This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Autonomous Vehicle by using 3D LIDAR and 2D CameraIRJET Journal
This document presents a study on developing an autonomous vehicle prototype using a 3D LIDAR sensor and 2D camera. The proposed system uses a Raspberry Pi as the main processing unit, connected to sensors like a LIDAR, camera, GPS and motor drivers. It aims to detect obstacles using these sensors and avoid collisions in real-time. The document discusses the various hardware components, system architecture, workflow and provides results from simulations and object detection tests on the prototype. It concludes that combining LIDAR and camera provides better environmental perception for autonomous navigation. Future work may include improving algorithms using advanced machine learning.
VEHICLE DETECTION USING YOLO V3 FOR COUNTING THE VEHICLES AND TRAFFIC ANALYSISIRJET Journal
This document discusses using YOLOv3 for vehicle detection and counting from video to analyze traffic. Video frames are used to identify moving vehicles and background extraction is applied to each frame to detect and count vehicles. YOLOv3 with a pre-trained model is used for object detection and classification of vehicles into classes like car, bus, motorcycle. Classification is shown for vehicles and individual types to analyze traffic levels. The analysis of vehicle levels is displayed using a pie chart.
Intelligent Traffic Light Control SystemIRJET Journal
This document proposes an Intelligent Traffic Light Control System (ITLCS) that uses cameras and deep learning to classify vehicles and dynamically adjust traffic light timings based on real-time traffic conditions. The system aims to reduce average wait times and account for changes in traffic to ensure optimal traffic flow and safety. It would require object detection using data acquisition and training a deep learning model to identify vehicle classes. Implementing ITLCS could address traffic congestion issues and reduce accidents at intersections by providing a more efficient alternative to traditional static traffic control systems.
This document provides a literature review of lane detection techniques for real-time road lane detection systems. It discusses how lane detection is an important aspect of intelligent transportation systems and driver assistance systems. The review covers various existing approaches to lane detection including image processing methods, edge detection, the Hough transform, and lane departure recognition. It identifies some limitations in existing methods, such as poor performance under difficult environmental conditions or on curved roads. The document proposes developing a new lane detection method to address these limitations and improve accuracy for real-time applications.
IRJET- Smart Parking System using Internet of Things TechnologyIRJET Journal
This document summarizes a research paper on a smart parking system using Internet of Things technology. The system uses sensors and cloud computing to determine available parking spaces and allow users to reserve spaces through a mobile app. This reduces traffic as users can find and pay for parking in advance instead of circling until an open spot is found. The system builds parking areas into an IoT network where data on space availability is continuously updated in the cloud and accessible to users. Research shows such smart parking systems can decrease the amount of time users spend searching for parking by 30% or more.
Congestion Control System Using Machine LearningIRJET Journal
This document proposes a machine learning-based system to address road congestion problems. It uses ML algorithms programmed in Python to develop automated traffic management solutions that can handle large volumes of traffic and ensure emergency vehicles like ambulances can move through congested roads quickly. The system detects vehicles like ambulances and motorcycles without helmets using object detection algorithms like YOLOv4. It recognizes license plates and sends violation notices to motorcycle riders detected without helmets. The system aims to provide priority to emergency vehicles at traffic lights using a Compact Prediction Tree algorithm based on deep learning. It analyzes previous research on dynamic traffic light control systems and proposes developing a continuous surveillance system and automated priority system for emergency vehicles.
The document discusses autonomous driving scene parsing through semantic segmentation. It begins with an introduction to autonomous vehicles and how they use sensors like cameras, radar and LiDAR to detect objects. It then reviews previous work on datasets for autonomous driving, semantic segmentation techniques like U-Net, and the need to study unconstrained environments. The paper proposes using the Indian Driving Dataset and a U-Net model with adjustments to perform semantic segmentation on Indian road scenes.
MACHINE LEARNING BASED DRIVER MONITORING SYSTEMIRJET Journal
The document describes a machine learning-based driver monitoring system that uses computer vision and machine learning techniques to analyze driver behavior in real-time, including gaze tracking, head movement, eye closure, and facial expressions. Sensors such as cameras and in-cabin sensors collect information on the driver's movements and environment. Machine learning models are trained to identify safety-critical occurrences like fatigue, inattention, and lack of focus. When risks are detected, the driver is promptly warned. The system aims to improve road safety.
This presentation talks about Software Defined Vehicles, Automotive Standards including Cyber Security and Safety, Agile Methods like SAFe/Less , Continuous Delivery best practices.
ROAD SIGN DETECTION USING CONVOLUTIONAL NEURAL NETWORK (CNN)IRJET Journal
This document presents a method for detecting and recognizing road signs using convolutional neural networks (CNNs). The method uses the German Traffic Sign Recognition Benchmark (GTSRB) dataset to train and test a CNN model for classifying images into 43 sign categories. The images are preprocessed by resizing to 30x30 pixels and splitting the training set into train and validation portions. The CNN is implemented in TensorFlow and achieves over 95% accuracy on both the training and test sets. The document concludes the proposed method provides an accurate and robust approach for automatic road sign detection and recognition.
IRJET- Traffic Sign Recognition for Autonomous CarsIRJET Journal
The document discusses a traffic sign recognition system for autonomous vehicles using a convolutional neural network. It begins with an introduction to traffic sign recognition and its importance for autonomous driving systems. It then discusses related works on traffic sign detection and classification, as well as machine learning approaches. The document outlines the proposed methodology, which involves using a CNN model to detect and classify traffic signs from image data. It then discusses the CNN architecture and training approach in more detail. Finally, it concludes that the system can help autonomous vehicles safely navigate by recognizing traffic signs and calculating the distance to the signs in real-time.
IRJET- Management of Traffic at Road Intersection using Software ModellingIRJET Journal
The document discusses various traffic simulation software that can be used for managing traffic at signalized intersections. It provides an overview of software tools like Aimsun, SIDRA, SUMO, and CORSIM that allow modeling traffic networks, signal timings, and evaluating performance measures. The document emphasizes that simulation software provide an understanding of traffic flow and interactions at intersections and are useful for testing design changes, signal optimization, and assessing different scenarios for improving traffic management.
Multiagent multiobjective interaction game system for service provisoning veh...redpel dot com
Multiagent multiobjective interaction game system for service provisoning vehicular cloud
for more ieee paper / full abstract / implementation , just visit www.redpel.com
IRJET- Self Driving Car using Deep Q-LearningIRJET Journal
This document describes a study on developing a self-driving car prototype using deep reinforcement learning. The researchers used a deep Q-network (DQN) algorithm to train an agent to control a simulated car directly from sensor inputs like cameras. The DQN was able to successfully navigate the simulated environment and control the car without any knowledge of its dynamics. While the discrete state-space DQN achieved stable control, the researchers believe the work could be extended to use continuous action spaces to allow for varying speeds and improved reward functions. The document also provides background on deep learning, autonomous vehicles, and reviews related work applying reinforcement learning methods to autonomous driving tasks.
IRJET- Traffic Sign and Drowsiness Detection using Open-CVIRJET Journal
This document presents a method for detecting traffic signs and driver drowsiness using OpenCV. It first preprocesses traffic sign images and extracts features using SIFT and DRLBP. Traffic sign detection is then performed using a backpropagation neural network. For drowsiness detection, the system continuously monitors the driver's eyes using a camera. It detects the open and closed state of the eyes to identify symptoms of fatigue. When the eyes are closed for too long based on a threshold, an alert is triggered to avoid accidents from drowsy driving. The proposed methods were tested on images and videos with promising results.
A Review: Machine vision and its ApplicationsIOSR Journals
Abstract:The machine vision has been used in the industrial machine designing by using the intelligent character recognition. Due to its increased use, it makes the significant contribution to ensure the competitiveness in modern development. The state of art in machine vision inspection and a critical overview of applications in various industries are presented in this paper. In its restricted sense it is also known as the computer vision or the robot vision. This paper gives the overview of Machine Vision Technology in the first section, followed by various industrial application and thefuture trends in Machine Vision. Keywords:CCD- charged coupled devices, Fruit harvesting system, HIS- Hue Saturation Intensity, Image analysis, Image enhancement, Image feature extraction, Image feature classification processing, Intelligent Vehicle tracking , Isodiscriminationn Contour, Machine Vision
IRJET- Advanced Waypoints Analytics for Automated DronesIRJET Journal
This document presents an algorithm for advanced waypoint analytics to automate drones. The algorithm takes grid coordinates as input, plots waypoints within the grid, and finds the shortest path connecting all waypoints using algorithms like dynamic programming and minimum spanning tree. It outputs the shortest path coordinates in a KML file for the drone to follow. The algorithm also incorporates various machine learning models to enable applications like predicting signal strength and diagnosing problems in telecommunication towers. This allows drones to perform tasks autonomously with minimal human input.
IRJET- Traffic Sign Detection, Recognition and Notification System using ...IRJET Journal
This document presents a traffic sign detection, recognition, and notification system using Faster R-CNN. The system takes video input containing traffic signs and converts it to frames. Faster R-CNN with ROI pooling and a classifier is used to detect traffic signs. Color and shape information are then used to refine detections. A CNN classifier recognizes the signs. The system notifies drivers of detected signs via audio messages, helping drivers comply with signs even if ignored visually. The proposed detector detects all sign categories, and recognition accuracy on the German Traffic Sign Detection Benchmark dataset exceeds 90% for 42 sign classes.
Advance Vehicle Advanced Driver Assistance Systems: Working & Features ADAS A...IRJET Journal
The document provides an overview of advanced driver assistance systems (ADAS) with three key points:
1. ADAS uses sensors like cameras and radar to help drivers and can detect things like lane departure, pedestrians, and oncoming collisions. This helps improve safety.
2. ADAS systems are classified as passive (warn drivers) or active (intervene in vehicle control). Examples of each are given.
3. The building blocks of ADAS including sensors, vehicle control, and processing are described. This technology is important for developing more autonomous vehicles.
Similar to A REVIEW ON MACHINE LEARNING IN ADAS (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Solving Linear Differential Equations with Constant CoefficientsIRJET Journal
1) The document discusses methods for finding the solutions to linear differential equations with constant coefficients. It defines such an equation and explains that the complete solution is the combination of the complementary function (C.F.) and particular integral (P.I.).
2) Various methods are presented for determining the C.F. depending on whether the roots of the auxiliary equation are real, imaginary, repeated, etc.
3) Rules are provided for obtaining the P.I. based on the type of function involved (exponential, trigonometric, power, etc.). Examples are worked through to demonstrate the full solution process.
Profiling of Cafe Business in Talavera, Nueva Ecija: A Basis for Development ...IJAEMSJORNAL
This study aimed to profile the coffee shops in Talavera, Nueva Ecija, to develop a standardized checklist for aspiring entrepreneurs. The researchers surveyed 10 coffee shop owners in the municipality of Talavera. Through surveys, the researchers delved into the Owner's Demographic, Business details, Financial Requirements, and other requirements needed to consider starting up a coffee shop. Furthermore, through accurate analysis, the data obtained from the coffee shop owners are arranged to derive key insights. By analyzing this data, the study identifies best practices associated with start-up coffee shops’ profitability in Talavera. These findings were translated into a standardized checklist outlining essential procedures including the lists of equipment needed, financial requirements, and the Traditional and Social Media Marketing techniques. This standardized checklist served as a valuable tool for aspiring and existing coffee shop owners in Talavera, streamlining operations, ensuring consistency, and contributing to business success.
Social media management system project report.pdfKamal Acharya
The project "Social Media Platform in Object-Oriented Modeling" aims to design
and model a robust and scalable social media platform using object-oriented
modeling principles. In the age of digital communication, social media platforms
have become indispensable for connecting people, sharing content, and fostering
online communities. However, their complex nature requires meticulous planning
and organization.This project addresses the challenge of creating a feature-rich and
user-friendly social media platform by applying key object-oriented modeling
concepts. It entails the identification and definition of essential objects such as
"User," "Post," "Comment," and "Notification," each encapsulating specific
attributes and behaviors. Relationships between these objects, such as friendships,
content interactions, and notifications, are meticulously established.The project
emphasizes encapsulation to maintain data integrity, inheritance for shared behaviors
among objects, and polymorphism for flexible content handling. Use case diagrams
depict user interactions, while sequence diagrams showcase the flow of interactions
during critical scenarios. Class diagrams provide an overarching view of the system's
architecture, including classes, attributes, and methods .By undertaking this project,
we aim to create a modular, maintainable, and user-centric social media platform that
adheres to best practices in object-oriented modeling. Such a platform will offer users
a seamless and secure online social experience while facilitating future enhancements
and adaptability to changing user needs.
Exploring Deep Learning Models for Image Recognition: A Comparative Reviewsipij
Image recognition, which comes under Artificial Intelligence (AI) is a critical aspect of computer vision,
enabling computers or other computing devices to identify and categorize objects within images. Among
numerous fields of life, food processing is an important area, in which image processing plays a vital role,
both for producers and consumers. This study focuses on the binary classification of strawberries, where
images are sorted into one of two categories. We Utilized a dataset of strawberry images for this study; we
aim to determine the effectiveness of different models in identifying whether an image contains
strawberries. This research has practical applications in fields such as agriculture and quality control. We
compared various popular deep learning models, including MobileNetV2, Convolutional Neural Networks
(CNN), and DenseNet121, for binary classification of strawberry images. The accuracy achieved by
MobileNetV2 is 96.7%, CNN is 99.8%, and DenseNet121 is 93.6%. Through rigorous testing and analysis,
our results demonstrate that CNN outperforms the other models in this task. In the future, the deep
learning models can be evaluated on a richer and larger number of images (datasets) for better/improved
results.
Natural Is The Best: Model-Agnostic Code Simplification for Pre-trained Large...YanKing2
Pre-trained Large Language Models (LLM) have achieved remarkable successes in several domains. However, code-oriented LLMs are often heavy in computational complexity, and quadratically with the length of the input code sequence. Toward simplifying the input program of an LLM, the state-of-the-art approach has the strategies to filter the input code tokens based on the attention scores given by the LLM. The decision to simplify the input program should not rely on the attention patterns of an LLM, as these patterns are influenced by both the model architecture and the pre-training dataset. Since the model and dataset are part of the solution domain, not the problem domain where the input program belongs, the outcome may differ when the model is trained on a different dataset. We propose SlimCode, a model-agnostic code simplification solution for LLMs that depends on the nature of input code tokens. As an empirical study on the LLMs including CodeBERT, CodeT5, and GPT-4 for two main tasks: code search and summarization. We reported that 1) the reduction ratio of code has a linear-like relation with the saving ratio on training time, 2) the impact of categorized tokens on code simplification can vary significantly, 3) the impact of categorized tokens on code simplification is task-specific but model-agnostic, and 4) the above findings hold for the paradigm–prompt engineering and interactive in-context learning and this study can save reduce the cost of invoking GPT-4 by 24%per API query. Importantly, SlimCode simplifies the input code with its greedy strategy and can obtain at most 133 times faster than the state-of-the-art technique with a significant improvement. This paper calls for a new direction on code-based, model-agnostic code simplification solutions to further empower LLMs.
A vernier caliper is a precision instrument used to measure dimensions with high accuracy. It can measure internal and external dimensions, as well as depths.
Here is a detailed description of its parts and how to use it.
Encontro anual da comunidade Splunk, onde discutimos todas as novidades apresentadas na conferência anual da Spunk, a .conf24 realizada em junho deste ano em Las Vegas.
Neste vídeo, trago os pontos chave do encontro, como:
- AI Assistant para uso junto com a SPL
- SPL2 para uso em Data Pipelines
- Ingest Processor
- Enterprise Security 8.0 (Maior atualização deste seu release)
- Federated Analytics
- Integração com Cisco XDR e Cisto Talos
- E muito mais.
Deixo ainda, alguns links com relatórios e conteúdo interessantes que podem ajudar no esclarecimento dos produtos e funções.
https://www.splunk.com/en_us/campaigns/the-hidden-costs-of-downtime.html
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-leading-observability-practice.pdf
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-modern-security-program.pdf
Nosso grupo oficial da Splunk:
https://usergroups.splunk.com/sao-paulo-splunk-user-group/