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Questions tagged [deep-learning]

a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hidden layers), but also with some sort of Probabilistic Graphical Models.

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Assistance Required with Python Project Setup

I am currently focusing on enhancing my skills in deep learning and have recently downloaded a project from GitHub to work on. Unfortunately, I am experiencing issues with getting the project to run ...
dreamv's user avatar
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Unordered Set Classification Problem

In my setup I have one feature which is a sparse list representing categories. For example, let's say that we have M categories in the interval ...
dpalma's user avatar
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How will weights learn in CNN for multi class classification?

How are the weights of filters in a CNN can learn meaningful features in multiclasses classification if they keep changing as different images are passed through the network during training.Say we are ...
Jai's user avatar
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Recreating results from Research Paper

so I have been trying to recreate the results from this particular paper (Neural Collaborative Filtering). The dataset I use closely resembles this . I understand that I should my data into train and ...
Panos_42's user avatar
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Create model for manufacturing defect detection using python

Has anyone done some work on manufacturer defect detection? I need some input on this. I have done some research and found some examples like TensorFlow/Keras and CNN, but I need some real-time ...
Reetesh Nigam's user avatar
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Tensorflow SegNet architecture

I was unable to find a complete description of the SegNet architecture for image segmentation (specifically, the decoder layers). Therefore, I would like to clarify the correctness of my ...
D .Stark's user avatar
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Extremely Imbalanced and Gapped Dataset in Regression Problem

Currently I am working with a biological dataset with a range of 0-to-1 to do a multi-task regression with Deep Learning. However, this dataset has an empty gap in the range 0 to 0.2 (however there ...
Abdullah Faqih's user avatar
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Trying to understand Ch.2.1 "2.1. Monads and their algebras" of "Categorical Deep Learning: An Algebraic Theory of Architectures"

I am trying to read article "Categorical Deep Learning: An Algebraic Theory of Architectures" https://arxiv.org/abs/2402.15332 and I am stuck with the Chapter 2.1 "2.1. Monads and their ...
TomR's user avatar
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DCGAN for mammograms

I'm currently working on a DCGAN with Wasserstein Distance Gradient Penalty (WGAN-GP) for mammograms. The target mammograms are in 4D, as I'm using SD VAE 1.4 to reduce the complexity. Each of the ...
Norhther's user avatar
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6 views

MIT-BIH and ECG-ID for ECG Authentication System

Both the MIT-BIH and ECG-ID data files are stored in the Waveform Database (WFDB) file format. The record_name.dat file formats are binary files containing samples of digitized signals. So, can I ...
Mohamed Azab's user avatar
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can we use tanh activation function to detect outliers?

Can we use tanh activation function to detect outliers ? Does my image below true for dataset outliers (after training model with tanh activation function) ?
user3668129's user avatar
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Best modelling method when target is a distribution

I have a regression task where each data sample is annotated by multiple (5-10) experts. I observe that the annotated target of each data sample is a Gaussian distribution. Usually, people will use ...
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I want to send parallel inputs to LSTM layers each LSTM layer should recieve 60 timesteps of single feature. How should i shape my inputs

...
Shreedatta Nasik's user avatar
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Are formulas in the article incorrect?

I am learning about backpropagation in LSTM. I have been studying an article and watching two videos on the topic. The videos 1 and 2 repeat all the information from the article, but with additional ...
Тима 's user avatar
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I am training LSTM model for flood water level prediction. How to make the performance of the model better?

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Param Thakkar VJTI CS's user avatar
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Resources for writing CNN for semantic segmentation

I am intermediate/advanced in Python and new to machine learning. Most of what I know about deep learning I learned through Deep Learning with Python by François Chollet. I am trying to do image ...
utx7563yu's user avatar
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graph signal in GNN

I am reading several materials about graph signal processing for a thesis on Graph Neural Network and i see that a graph signal is defined as a vector so each node signal is a scalar. In practice, a ...
endeavor's user avatar
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How to properly prune a YOLOv8 model

I was trying to apply pruning to a YOLOv8 detection model. Following is my code and it runs successfully. I see the saved pruned model as well. My YOLOv8 model has 22 layers (an example list of layers ...
Mary H's user avatar
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How to improve Accuracy on dermaMNIST dataset?

Unlike the regular MNIST which gets 97-99% with a fairly basic network, dermaMNIST gets training/validation stuck on 0.69. This tells me the model is underfitting. But, making it bigger seems to have ...
Zwerchhau's user avatar
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Why did I got opposite results of the original "How transferable are features in deep neural networks" paper?

I got tasked with reproducing the results of the influential "How transferable are features in deep neural networks?" paper in a DL class I'm taking (Full code). I got the exact opposite ...
OfirD's user avatar
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LSTM, different size for feature set and target

I am trying to build a weather forecasting model. X_train shape :(2970, 1, 9) Y_train shape : (3299675, 1, 4) I am following ...
Abhishek Patil's user avatar
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1 answer
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Why are some columns of feature matrix after dimentionality reduction zero?

I am trying to implement a paper in which the ultimate goal is to predict mutliple labels for instances (which are genes here). The feature matrix with shape of 1236*18930 is built by calculating term ...
Satarnejad's user avatar
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Keras Tuner for a (stacked) LSTM model?

I have a question about how to correctly setup a Keras Tuner model for a stacked LSTM model. What I have tried is the normal tutorial with a loop and the hp.Int() function to define the size of each ...
Barry's user avatar
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1 vote
1 answer
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How to Balance Dataset extracted using image_dataset_from_directory

I'm new to tensorflow, so I've been trying to find the best way to do class balancing over a dataset where I used image_dataset_from_directory to load. But I haven't find the way to do it. I saw from ...
lopez-mgu's user avatar
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21 views

Validation loss not decreasing

I am building a model for predicting stock portfolio positions, by minimizing a Sharpe loss function (corresponding to maximize the Sharpe ratio of the portfolio). The architecture is puting ...
Dan Lee's user avatar
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58 views

How to prune my Yolov8 object detection model?

I trained a yolov8-medium object detection model, but I'm not sure how to apply pruning on it. What is the proper way to prune it? I got this example code, but it only looks for ...
Mary H's user avatar
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1 answer
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How to interpret annotation data?

I am new to datasets. I have got an annotations train.json for MR image data like this - I want to train a Yolo-V8 model using this MR data images extracted from dicom raw data and annotations for ...
mrin9san's user avatar
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1 answer
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LSTM predicted negative values although the training data are all postive values

I am training LSTM to predict tree sap flow (30 min interval). I am keeping getting negative predictions, although the most of the predictions look good. I tried to use different scalers for ...
Jiaj's user avatar
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1 answer
14 views

Understanding batching in pytorch models

I have following model which forms one of the step in my overall model pipeline: ...
Mahesha999's user avatar
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22 views

While working on binary image classification, the class mode set to binary incorrectly labels the images, but does it correct on categorical

I am currently working on a binary image classification. My problem is that when i use data augmentation, it incorrectly labels the images when it is set to binary. The things i have tried: Looked ...
Enes Aygun's user avatar
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0 answers
6 views

Speaker Verification models on

I went through different articles of speaker verifications (ECAPA-TDNN, TITANET). They trained on ...
user3668129's user avatar
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12 views

Decreasing reward when using DDPG

When I try to use the DDPG to solve a problem about resource allocation in communication networks, I get an odd result, e.g., the reward becomes smaller and smaller. At the same time, the critic's ...
Baolin Yin's user avatar
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Can someone interpret my Binary Cross Entropy Loss Curve?

I am trying to understand my loss curve using : tf.keras.losses.BinaryCrossentropy() Question 1: Based on my loss curve/accuracy, would it be wise to proceed to feed it into a ensemble learning model ...
Leibon Jarbis's user avatar
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34 views

deep learning for stock prediction

I am learning deep learning . Right now I am using MNIST data set, which contains tens of thousands of scanned images of handwritten digits, together with their correct classifications. My question ...
quanity's user avatar
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24 views

Combining monte carlo with deep learning to improve the estimation

I am in situation where i need to estimate the attenuation of an EM wave . we consider EM wave as collection of photons. These photons when strike with some dust particles they scatter in different ...
user7341333's user avatar
1 vote
1 answer
26 views

Asynchronous Training of Deep Learning Models

I am thinking of how would it be if I can create asynchronous forward function in sub-class of nn.Module . When I came across architecture in attached image, I felt that it would be faster if we could ...
Sarvagya_P's user avatar
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Insights about W0rd2Vec

As per my knowledge, Word2Vec is belongs to non-contextual embedding technique. this have only semantic relationship between words. We can implement Word2Vec, either in CBoW or skip-gram model. but i ...
Tovlk's user avatar
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1 answer
18 views

Which Experiment Results Should Be Included: Reproduced or Original?

I am currently working on a research project in the field of machine learning where I am attempting to reproduce the results of a specific paper. To ensure accuracy and transparency, I have utilized ...
jackson's user avatar
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1 vote
1 answer
61 views

How is openAI embedding models trained?

how it the embedding model trained? Are the embeddings simply extracted from chatGPT4 or are they trained differently from the beginning (pre-training stage)?
haneulkim's user avatar
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Finding invariant feature areas within representation vector for each meta-class/group?

I have pairs of images which are not the same class, but are from the same meta-class/group. I have a standard CNN which produces a representation for each sample. If I have several pairs of images ...
StudentV's user avatar
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1 answer
19 views

Question about contextual embeddings?

How do BERT and RoBERTa generate contextual embeddings? The articles I've read keep saying that transformer encoders work bidirectionally. Because of self-attention, they can look at every token, ...
abcd's user avatar
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0 answers
21 views

Is the score function form of ALiBi, a positional encoding in Deep Learning, always lower triangular?

I have a question about the score function of ALiBi (Attention with Linear Biases), which is a positional encoding method introduced by the following paper: TRAIN SHORT, TEST LONG: ATTENTION WITH ...
shx's user avatar
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4 votes
2 answers
99 views

What is the best way to train a neural network with a variable number of inputs?

Suppose I have a neural network with 5 inputs: [A,B,C,D,E] There is only 1 output. The expected accuracy of the model should increase when all 5 inputs are ...
user18959's user avatar
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0 answers
6 views

dimensions conflict when trying to use a pretrained wav2vec2-xls-r-300m model

i am trying to use a pretrained model facebook/wav2vec2-xls-r-300m and fine tune it for audio classification and more specifically emotion recognition. i am using an audio labeled dataset ( 12 labels )...
stanley101's user avatar
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0 answers
16 views

Trained model on cifar10 performs poorly on real images

So I'm trying to train a model using the CIFAR10 dataset. The problem is that while the performance of the model on validation and test sets are good (about 95-96%), the model fails to predict images ...
AlbertDang's user avatar
1 vote
0 answers
19 views

Improving Detection Model - Adding image clarification

I trained an object detection model with 5K images, it works most of the time, but I am facing an issue, for few times, the object is not getting detected. So, I planned to retrain the model, for that ...
Vishak Raj's user avatar
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0 answers
8 views

Model for k means clustering of last mile logsitics data set

I want to utilize Orange for K means clustering for Network Design for Courier Company using K means clustering. Data set includes Longitude & latitude of delivery points, parcel weight, area type ...
asdcxbx's user avatar
4 votes
1 answer
97 views

LLMs for text generation

We know that AI is rapidly growing. do we have any large language models (LLMs) to process images, pdf documents directly (fine-tune approach) for text generation tasks?
Tovlk's user avatar
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i need to improve accuracy of following code. it have 1 dataset folder having 7 folders. there are total 3076 images

importing libraries ...
raman deep's user avatar
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0 answers
10 views

How to assess the stability of a DL model, after using k-fold cross-validation for hyperparameter tuning

I've recently completed the training of a deep learning model for a classification task, using a process that involves k-fold cross-validation for hyperparameter tuning Initially, I have divided my ...
o'hara's user avatar
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