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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Am I using transfer learning when I use SSD ResNet 50 model architecture?

Using Label-img, I have successfully labeled my images (dimensions 1100 x 1100 pixels), and am currently training the SSD ResNet50 model (from the TensorFlow 2 Detection Model Zoo). I downloaded the ...
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14 views

Does a Siamese Network need other trainable layers after the distance layer?

I'm approaching at Siamese Networks in order to use them for Image Similarity. I found that many people use famous models like VGG or ResNet to build the vectors that will go on the distance layer in ...
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130 views

How to determine the number of fully connected layers for a convolutional neural network?

How many fully connected layers should be added to a convolutional neural network? Does it depend on input size to the fully connected layer? If so, how do we decide? What if the input size of the ...
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21 views

CNN to detect presence/absense of label on images with mixed labels

Here's my problem: I work with medical image classification, and currently I have 3 classes: class A: images with lesion 1 only; and images with lesion 1 and N other lesions class B: images with 2 ...
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25 views

How does scheduled sampling for transformers work?

I was reading this paper which applies a modified version of the transformers for traffic forecasting. I am somewhat familiar with the transformer architecture and how it functions, but, in the paper, ...
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39 views

Is Webpage Semantic Segmentation possible nowadays?

I'm trying to do some research about semantic segmentation for webpages, in particular e-commerce webpages. I found some articles which provide some solutions based on very old dataset and those ...
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10 views

Is there a framework or method that would help visualise inner workings of a feedforward neural network?

I wonder if there is some framework or method to help visualising inner workings of a feedforward deep neural network? What I mean by this is something similar to what is being done with CNNs where we ...
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37 views

How to use Deep Q-Network with two-dimensional input? Hands-on Machine Learning 2

I'm studying with the book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow, and I'm trying to implement the Deep Q-Network example that can be found on Github but that the input ...
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49 views

Deep Learning based image restoration using multiple frames

Suppose we have a sequence of still images each of which has been contaminated by some particles(ex, dust/sand/smoke) making the images very poor in certain areas. What architecture would be best to ...
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29 views

XOR problem with bipolar representation

I am taking a course in Machine Learning and the Professor introduced us to the XOR problem. I understand the XOR problem is not linearly separable and we need to employ Neural Network for this ...
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29 views

Extracting specific information from an Invoice images

Tried to extract only specific information from the images but Couldn't, We have to automate this process using this as the format of the Images keeps on changing. LinkSample data What I have Tried: <...
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56 views

How long will it take to train SSD V1 Mobilenet image recognition algorithm?

I am training a deep learning algorithm using an NVIDIA GEFORCE RTX GPU, with 16 GB RAM. I went through my image database and generated 50,000 training samples with the Labelimg software; the images ...
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29 views

How did they use their dataset with VAEs?

Old Photo Restoration via Deep Latent Space Translation (https://paperswithcode.com/paper/old-photo-restoration-via-deep-latent-space) In the article, it says : "We propose to restore old photos ...
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27 views

Wasserstein GAN with gradient penality - Loss values

I have trained a WAN with gradient penalty and the loss values ​​seem to me much higher than the examples I have seen on the net. The generator receives 2 images as input and must generate a ...
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38 views

Deep Continuous Clustering algorithm - just one output cluster

I use the DCC algorithm to cluster some data. The whole algorithm is available here, but shortly it is: construct mkNN graph of the data points (the connected components of it are the clusters). ...
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32 views

Choice of loss function for semantic segmentation

I am training a U-Net for semantic segmentation of large medical images (4096x4096px). The two classes are "too" unbalanced. The white pixels are just about 0.1% (or less) of the whole image....
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64 views

Multi-label dataloading bottleneck Pytorch

I am trying to write custom dataset and dataloader for pascal-voc-2007. It is a multi-label classification problem. There is csv file to hold the name of the images and their corresponding labels. I ...
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36 views

Deep learning based physics engine

Ridgid body simulation is a well known field with well established methods. It's still fairly computationally expensive to simulate things. I am interested in approaches to training deep learning ...
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8 views

Need some help in understanding a Research paper on Auto Image Colorization

I am having trouble understanding implementation of a research paper. Paper I need assistance in the 3.6 Final Classification Model on page 3. How exactly should the pixels be discretized into 50 bins?...
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22 views

What are some good models to use for spelling corrections?

I used OCR to extract text from an image, but there are some spelling mistakes in it : The text is as follows : ...
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28 views

How to use SPP-net and what are its drawbacks?

I read about the spatial pyramid pooling concept, it's really cool! Now, my doubt is how to find the number of layers to use, and in each layer what should be the grid sizes when using spp. But, I ...
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43 views

How to use a NN for seq2seq tasks?

I am trying to make a NN(probably with dense layers) to map a specific input to a specific output (or basically sequence2sequence). I want the model to learn the relation between the sequences and ...
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18 views

Strategy to input and get large images in VGG neural networks

I'm using a transfert-style based deep learning approach that use VGG (neural network). The latter works well with images of small size (512x512pixels), however it provides distorted results when ...
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15 views

Is there a model suitable to predict one correct value based on a 2D input series?

I am using an encoder-decoder architecture, with 2 layers each in the encoder and decoder and 128 neurons in each hidden layer. The inputs are in a 2D form: one column has the days and the other ...
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30 views

Confusion on Math Notation Definition

I attempt to understand the formulation of dictionary learning for this paper: Depression Detection via Harvesting Social Media: A Multimodal Dictionary Learning Solution Multimodal Task-Driven ...
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59 views

What prerequisite knowledge should I have to learn about neuromorphic chips and computing?

What prerequisite knowledge should I have and what are the best resources to learn about neuromorphic chips/computing on a deep, technical level? I would like to understand everything from the ...
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18 views

Calculating processing time of a deep learning model

My model deals with videos, and I want to calculate how fast it can process frames as in frames per second or processing time for 1 frame. I have made a single function to get predictions, it takes in ...
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21 views

How can I calibrate 3 cameras and track the object using only synchronized cameras feeds from all the cameras?

I have camera feed (in the form of RGB images) from 3 cameras with partially overlapping Field-of-view i.e. for the time stamp 0 to 100, I have total 300 frames or say synchronized 100 RGB frames for ...
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50 views

Logistic Regression or General Machine Learning Model using Federated Learning

Past few days I am doing some research on Federated Learning. I got many solutions with MNIST dataset using Nural Net but I am thinking to solve some common Machine Learning problem like Churn ...
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28 views

Keeping track of multiple faces throughout a video

I have a video where multiple persons are seated. I need to keep track of the emotions they show throughout the video. My final result should be a csv file with all the emotions depicted by each ...
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28 views

Structure for neural network

My purpose is to apply deep learning for planning. To do so, I decided to use a similar approach as AlphaGo. But my "game state" is very different. Instead of considering some planes ...
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1answer
24 views

How to train the images of various sizes?

I am practicing with an image dataset which is having different dimensions. If I simply crop and pad them to 1024X1024(the original images having smallest width is around 300 and largest is around ...
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16 views

How can I decrease the time to compute the mask in the Mask-RCNN for human body detection?

I am using Mask-RCNN to detect human bodies in photos, to get a rough approximation of the ratio of their heights to the length of their chests. I want to decrease the time for making the mask of the ...
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15 views

Are there any deep learning tools so that can be used to estimate long-tail distributions?

Are there any deep learning tools so that can be used to estimate long-tail distributions? update: my context is there are is there is a long-tail distribution (probability distribution) in my data of ...
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Why it is reshaped the last layers of VGG_UNet segmentation model?

I want to do a multiclass segmentation task using deep learning (in python). Here, is a summary of vgg_unet model that is mainly collected from GitHub. So, in my dataset 8 labels are available. So, at ...
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25 views

Does a constant low validation loss mean great model accuracy?

This is more of a conceptual question that I am asking here. I am using an encoder-decoder model with Bidirectional LSTMs used as a time series regression problem. I train it with a sufficiently low ...
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11 views

Generative Adversarial Network with two images in input

I am doing an internship project regarding deep learning, and it is a totally new topic for me as I have never studied machine learning in the bachelor's degree courses. I have to implement a GAN that ...
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47 views

Why does my loss value of autoencoder in PyTorch is negative?

I am trying to implement SDNE, a algorithm uses deep auto encoder to map a graph to latent representation d dimension. The idea is kind of simple, SDNE uses the ...
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1answer
37 views

How can I implement 2D CNN filter with channelwise-bound kernel weights?

I would like to bind kernel parameters through channels/feature-maps for each filter. In a conv2d operation, each filter consists of HxWxC parameters I would like to have filters that have HxW ...
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17 views

Transfer Learning: Finetune a model with a splitted dataset?

Lets say I want to fine-tune a model. I have a pretrained ResNet model and on top of this model I add some extra layers. And lets say I have a dataset of 10,000 images. The recommended way would be: ...
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1answer
169 views

What is the state-of-the-art algorithm for neural style transfer?

I've read the paper A Neural Algorithm of Artistic Style by Gatys et. al. and I find the application of neural style transfer very fun. I also read that Exploring the structure of a real-time, ...
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44 views

How to add voice inflections to an existing SV2TTS voice cloning implementation?

I've been playing with the SV2TTS voice cloning implementation provided on Github: https://github.com/CorentinJ/Real-Time-Voice-Cloning It was straight forward to use as a TTS engine with clearly ...
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21 views

What are some solutions for dealing with time series data that are recorded at uneven intervals?

Let's say I have a time series data which is a bunch of observations that occur at different time stamps and intervals. For example, my observations come from a camera located at a traffic ...
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27 views

Is Bayesian NN vs adding random data more accurate?

I’m trying to train a classifier to recognize if people are wearing seatbelts. What if the person submitted a picture unrelated to a seatbelt classifier? Would I create an image label that is full of ...
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36 views

Why do we use the Target Network for action evaluation in Double deep Q networks

Is there any specific reason as to why The target Network is used for evaluation and The online network Is used for selection, what would be the difference if both roles were switched, our online ...
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39 views

Having trouble understanding how Double deep Q networks work

I’ve looked at various articles and I’m still very confused, I understand the normal double Q learning about having two Action value estimates that use two different set of samples But coming to ...
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48 views

What is the reason for implementing position-wise Feed Forward Network in Transformer?

Does anyone know the reason why there's a FCNN after the self-attention layer? Or at least some intuition for it?
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35 views

Is it a good idea to train a neural network to classify images without base-hypothesis?

I'm a relative beginner in deep-learning (understand by that, I'm doing my first kaggle competition right now, and I have loads to learn still) and I was just wondering something. Let's say you have ...
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45 views

Possible reasons that validation recall is fluctuating across different epochs but the precision is stable?

I'm training a deep learning model. After each epoch I measure the performance of the model on validation set. Here is how the performance looks like while training: It's a binary classification task ...
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70 views

What could be the possible strategy and Deep Learning method that MathPix might be using for LaTex detection?

I want to build an open Source OCR just like MathPix. There is already a model to extract LaTex from the image by Harverd NLP's im2markup but the problem is that their data has been trained and tested ...

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