Questions tagged [deep-learning]
For questions related to deep learning, which refers to a subset of machine learning methods based on artificial neural networks (ANNs) with multiple hidden layers. The adjective deep thus refers to the number of layers of the ANNs. The expression deep learning was apparently introduced (although not in the context of machine learning or ANNs) in 1986 by Rina Dechter in the paper "Learning while searching in constraint-satisfaction-problems".
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Detecting unknown defects in components using deep learning methods
The problem:
We need to determine from images of technical components whether the components are defective or not. We don't have images of defective components, and we can't know in advance what kinds ...
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Generation of text describing moving objects in video
How might I generate text messaging from live video describing how objects of significance are moving, left, right, away from me, in or out of a building etc., without using lidar or similar to assess ...
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What is the reason for the difference between the expected input tensor order for LSTM and Conv1d?
What is the reason for the difference between the expected input tensor order for LSTM and Conv1d?
Say I have an input tensor for time series data of shape ...
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How to quantify the tone of a textual paragraph? If there is historical communication available, how to check for consistency in tonality for new i/p?
Certain aspects of NLP such as the basic Polarity, Subjectivity, and Positivity, can be obtained with ease, but keyword consistent usage and the "Style" or the "Tone" of writing ...
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Does Machine Learning focus on discriminative AI while Deep Learning also focus on generative AI?
I know that Deep Learning is subset of Machine learning
But is it correct that classical ML algorithms mainly focus on implementing Discriminative AI while DL algorithms implement both Generative AI ...
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Image Augmentation for Leaf Disease Detection: Training or Testing?
I am working on a leaf disease detection project and evaluating different strategies for augmenting the existing dataset to improve model performance. However, I am facing some confusion. Should I ...
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Is training two models of deep learning is considered as end-to-end learning?
Suppose there is binary classification problem, that's mean the output is scalar.
Suppose the input is vector that accepts 512 elements.
First model is trained for preprocessor, and the second one for ...
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Why time based neuron still needed when the time-series data can be converted to time-freq domain (image) and use CNN for that?
LSTM, BI-LSTM, GRU, RNN are time-step based neuron. Why it still needed specifically for time-series data?
I mean, we can just transform the time-series data into spectrogram and use CNN for that.
For ...
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Troubles using unsupervised domain adaptation
Hope somebody can help me, I've been stucked on this and there's no way I can find the origin of my problem...
So I have a model that I have fine-tuned, it's a resent18 that looks like this (I'm just ...
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Using conditional probability as an estimate in a loss function
I have a rather large ML framework that takes multiple conditional probability terms that are computed via classifiers/neural networks. This arbitrary loss function is computed via a function:
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Interpreting Physics Informed Neural Network Coefficient Estimates
I am currently trying to understand and interpret a PINN model I have built, I am just a bit confused on how to correctly interpret the coefficient estimates.
Let's say my ...
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Clarification on why Deep Learning works from Goodfellow's book
I am reading the section 5.11.2 from the Deep Learning book where the authors explain Deep Learning can deal with high dimensionality data in contrast to classical machine learning algorithms. However,...
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Neural network with a variable # of neurons
Hello I want to design a AI.The neural network of my AI will consist of 1 input layer of neurons and 1 output layer.
What is very unique about the neural network is that the # of input neurons will ...
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Do We Still Need to Learn About Boltzmann Machines?
When looking at the deep learning courses offered by top universities in the United States that are available online (not MOOCs, but actual classes), a few schools still cover (Restricted) Boltzmann ...
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Is deep learning suitable/preferable for string similarity detection and application automation? If so, which type?
newbie here. I have developed an app that basically does:
Perform OCR, check if words are contained in the resulting text and then perform an action.
If no words are detected from the given list, ...
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