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.

Filter by
Sorted by
Tagged with
0
votes
1answer
20 views

model has not yet been built

I'm making CNN-LSTM model for forecasting but I'm receiving this error : This model has not yet been built. Build the model first by calling build() or calling fit() with some data. Or specify ...
2
votes
0answers
29 views

Setting BATCH SIZE when performing multi-class classification with imbalanced dataset

I have a question regarding BATCH_SIZE on multi-class classification task with imbalanced data. I have 5 classes and a small dataset of around ...
2
votes
0answers
13 views

LSTM low training/validation error but really bad predictions

I'm building a LSTM model to create an automatic drums composer. I'm following this post: LSTM Metallica I've built my model and done all the enconding, I was able to emulate the behavior of the ...
1
vote
1answer
35 views

How to reduce overfitting in a pre-trained network

I have a custom dataset with 10 classes and I am using a pre-trained resnet18 model from torch-vision. I can clearly see it's over-fitting because: the model is trained for 75 epochs with a batch size ...
1
vote
0answers
33 views

Error when checking target: dimensions error in CNN-LSTM model for multivariate time series forecasting

I'm making a CNN-LSTM model to forecast multivariate time series: ...
1
vote
0answers
15 views

Fine tuning Conditional GANs for low data scenarios

I was wondering what the process was for fine tuning a conditional GAN. For example, say I wanted to generate pictures of an object X given a certain condition such as a sentence describing it, which ...
2
votes
1answer
23 views

How is GPT able to handle large vocabularies?

From what I understand, GPT and GPT-2 are trained to predict the $N^{th}$ word in a sentence given the previous $N-1$ words. When the vocabulary size is very large (100k+ words) how is it able to ...
3
votes
0answers
16 views

How respective gating functions are ensured in LSTM?

I'm studying the Hochreiter-Schmidhuber long-short term memory recurrent architecture. The overall idea, information flow and manipulation is clear, and it seemingly works, but what I cannot ...
4
votes
3answers
397 views

Topics to learn in Neural Network [closed]

I have recently started learning Deep Neural Networks and was going through the tutorials online. Everywhere I saw that the topics post Image classification using CNN is a little hazy. No one seems to ...
1
vote
1answer
26 views

Time series binary classification [closed]

Which deep learning architecture and algorithms do you most recommend for time series classification problem? Of course LSTM, I am looking for state of the art papers.
3
votes
0answers
29 views

AlexNet Research Paper VS PytTorch and Tensorflow implementation

I'm making my way through Deep Learning research papers, starting with AlexNet, and I found differences in the implementation of PyTorch and Tensorflow that I can't explain. In the research paper, ...
3
votes
3answers
40 views

How does “ Sparsity of connections” in CNNs causes the network to have less parameters?

I am studying Andrew NG's lectures on Convolutional Neural Network and he had provided two reasons for CNNs having less parameters compared to Non-Convolutional networks . They are : Parameter ...
10
votes
7answers
312 views

Multi-country model or single model

I am working on a ML model to be deployed in a product operating in many countries. The issue that I am having is the following: should I train one model and serve it for all countries? train a model ...
0
votes
0answers
16 views

Using deep learning or statistical tools to complete physical equation

I need to predict a continuous variable Y in a regression setting. Theory in the field tells me it should follow an equation of the form: $$Y=g_0(X)-f_1(X)g_1(X)-f_2(X)g_2(X)$$ Where X is a vector of ...
0
votes
0answers
17 views

DICE loss too low but no overlap between prediction and label

I am trying to achieve the segmentation of the bone on the cross sectional area of MRI images with the Unet I found here. The label is a binary png image which I intend to compare to my prediction. ...
2
votes
1answer
29 views

What do `loss` and `accuracy` values mean?

I'm using this: Python version: 3.7.7 (default, May 6 2020, 11:45:54) [MSC v.1916 64 bit (AMD64)] TensorFlow version: 2.1.0 Eager execution: True With this U-Net ...
0
votes
1answer
26 views

How to input LSTM output to MLP with concatenate?

I am having a training data set for a time-series dataset like below where my target variable is var1(t) which is the value of var 1 at time=t. ...
1
vote
0answers
14 views

Custom GRU With 3D Spatial Convolution Layer In Keras

I am trying to implement a custom GRU model that is shown in this paper 3D-R2N2 The GRU pipeline looks like: The original implementation is theano based and I am trying to apply the model in tf2/...
0
votes
2answers
23 views

Why are RNNs used in some computer vision problems?

I am learning computer vision. When I was going through implementations of various computer vision projects, some OCR problems used GRU or LSTM, while some did not. I understand that RNNs are used ...
0
votes
2answers
15 views

What does it mean when the shape of input images is (600,64,64,3)?

While attempting an assignment, I found that shape of the input image was (600,64,64,3). I thought 3 stood for the number of channels but it's listed as the 4th dimension. What does this mean? This is ...
1
vote
0answers
36 views

What AI model should I build to find out how similar are the 2 audio files of musical instruments like piano, guitar, synthesizer?

I have a idea for a project in AI, and I want to know how can I build such kind of AI models. I have good understanding of ML, and some beginner level understanding of Deep learning. What should I ...
0
votes
0answers
11 views

Unrelated output by pytesseract image_to_string function

I'm trying to extract text from an image but pytesseract is giving a totally different output, the image attached below output is "Werle" (complete different word and characters), I tried ...
-1
votes
1answer
15 views

How to run Neural Net on GPU without python frameworks?

I coded a deep learning model from scratch in python(using numPy) without using any frameworks like keras or tensorflow. So far my model works fine but it runs on CPU. How should i modify my code so ...
1
vote
1answer
32 views

How is vector A converted to single value scalar in Andrew Ng's course?

In Andrew Ng's deep learning course on Coursera, how is a single scalar value obtained from a flattened image (feature vector)? First there is $w.T$ of shape $(1, n_X)$ which is multiplied by $X$ of ...
1
vote
0answers
10 views

How to properly train CNN on Full Digital Mammography

I am trying to train my Convolutional Neural Network on full digital mammography images. Here are example dimensions from a random sample: (5832, 4104, 3). Which ...
0
votes
0answers
14 views

How do I efficiently load data from disk during training of deep learning models in pytorch?

I'm trying to train a deep learning model without loading the entire dataset into memory. My main question is, what's the best way of doing this? It seems like HDF5 is a common method that people ...
1
vote
1answer
18 views

what is the difference between positional vector and attention vector used in transformer model?

what is the difference between positional vector and attention vector used in transformer model ? , i saw a video in youtue and the defintion for positional vector was give as :* "vector that ...
0
votes
1answer
55 views

Bert-Transformer : Why Bert transformer uses [CLS] token for classification instead of average over all tokens?

I am doing experiments on bert architecture and found out that most of the fine-tuning task takes the final hidden layer as text representation and later they pass it to other models for the further ...
2
votes
1answer
23 views

Does NER work on large documents around 1500 - 3000 words or so?

Let's say I have a resume and I have segmented the work section. Usually work section of resume contains company name, designation, work period and job description. ...
0
votes
0answers
10 views

How to draw multiple matrices (with grid, custom color per cell) in 3D with raycast?

I would like to draw multiple matrix with ray-casting in 3D. More specific like this (source) I have seen similar figure in some paper (I forgot which one). I wonder how they can draw like this. If ...
-1
votes
1answer
14 views

Using LSTM to predict next word performs poorly

I am training a model to predict the next word in a sequence, my data is comprised of Reddit post titles and is structured as: ...
0
votes
0answers
20 views

Construction of a three variable function from a set of given data points

For my problem a function $\phi$ takes three variables $f(\mu,\nu,\rho)$. Suppose, we know the range of the parameters value of $\mu=[-3,3]$, $\nu=[-3,3]$ and $\rho=[-3,3]$. We have functional value ...
0
votes
0answers
17 views

Python Ludwig: interpretation of final coding metric

I am learning über ludwig in Python. I ran the yaml definition file. I sat the epochs to 10. I have attached the screen shots of last 4 epochs. Screen shot 1 Screen shot 2: After running the program,...
1
vote
1answer
36 views

LSTM-Model - Validation Accuracy is not changing

I am working on classification problem, My input data is labels and output expected data is labels I have made X, Y pairs by shifting the X and Y is changed to the categorical value ...
0
votes
0answers
9 views

LSTM Neural Network gets stuck in a specific state when trying to predict new states over many time periods

I have built an LSTM neural network for category, or latent state, prediction. The data is more or less of the form: x1 = continuos number from current record x2 = continuous number from current ...
2
votes
2answers
32 views

Build neural network to calculate points for a board game

I want to be able to calculate how much points each player has for a board game by taking a picture on the board game. I do this as hobby, not for university or professional purposes. I will use it ...
1
vote
1answer
14 views

Should the weights for CrossEntropyLoss be exactly the inverse of the propotions of training data?

I have a classifier network which chooses one of three classifications, and uses cross entropy loss as the loss function. If the proportions of training data are 100:10:5 for each classification, ...
1
vote
2answers
34 views

Why my training and testing set are about 99% but my single prediction does wrong prediction?

I have performed fruits classification using CNN but i am paused at a point where all things are going right confusion matrix accuracy score all are correct it seems there is no overfitting but it ...
0
votes
0answers
11 views

Are there any techniques to explore the inter - target correlations and the input - output correlations in the Multi Traget Regression Problem

I am working on the Multi target regression problem in which there are 4 target variables and 17 input features. I tried to use hard parameter sharing method to predict the target variables. I am ...
2
votes
0answers
32 views

Where can i download a benign PE dataset? or at least which website is the best candidate for crawling and downloading normal executables?

I'm planning to gather a benign dataset for my ML malware detection model the problem I'm having is finding benign PE files, i just need a source that has a dataset of normal executables, i will scan ...
0
votes
2answers
34 views

Python: advice on which machine learning algorithm to use for a problem which involves lots of randomness

I'm new to machine learning so I'll summarize my problem with two examples without getting technical (because I can't). The dog vs. cat classification example is solvable, in the sense that a human ...
2
votes
1answer
41 views

How to build recommendation model based on resume and job description?

How to build a model which will result in better recommendation of resumes based on the job description given? I am familiar with bow or tfidf (n-grams) approach and then take a cosine similarity but ...
0
votes
0answers
28 views

How to deal with severe overfitting in a UNet Encoder/Decoder CNN in a task very similar to image translation?

I am trying to fit a UNet CNN to a task very similar to image to image translation. The input to the network is a binary matrix of size (64,256) and the output is of size (64,32). The columns ...
0
votes
0answers
30 views

Is it true more CPU core is better for deep learning?

I just started to learn the deep learning in my free time. I was hoping to buy a laptop where I want to implement some small(alexnet) to medium(GoogleNet) networks maybe something bigger. I searched ...
0
votes
1answer
21 views

Varying Image sizes in Tensorflow Malaria dataset | Dealing with unclean tensorflow data

I am trying to build a CNN based image recognition system for the Tensorflow malaria dataset. I loaded the dataset (~27k RGB images) using conventional tensorflow_datasets syntax. After some data ...
1
vote
1answer
13 views

How do I get one overall prediction, where each data point has many pictures?

My task is not a simple image -> category. I have between 5 and 10 images of an object, and I must classify it. The problem is that the category isn't "...
1
vote
1answer
38 views

Is it true more CPU core is better for deep learning?

I just started to learn the deep learning in my free time. I was hoping to buy a laptop where I want to implement some small(alexnet) to medium(GoogleNet) networks maybe something bigger. I searched ...
0
votes
0answers
23 views

How to interpret curve of regularization loss during CNN training?

I am fine-tuning a single shot detector (SSD) in tensorflow object detection api. I didn't freeze the backbone (mobilenet), I programmed the learning rate to go from e-3 to e-4 to e-5. In the paper ...
0
votes
0answers
16 views

How to interpret hard negative mining curves while training a deep object detector?

I am training a single shot detector (SSD) in tensorflow object detection API. After having read the paper and some articles online, I understood that hard negative mining trains the network on 'hard ...
2
votes
3answers
44 views

Should you turn off label smoothing when validating?

As the subject says. On one hand, the answer should be yes because label smoothing is a regularization feature and how can you know if it improves performance without turning it off? On the other hand,...

1 2
3
4 5
66