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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Can not install spacy package on windows 10 via pip
I have below environment.
OS: Windows 10
Python: Python 3.7.4
PIP: pip 19.3.1
I am trying to install spacy in my windows 10 OS. It gives me below error.
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how do I label my images for computer vision
So I want to do shape recognition task on a flowchart using CNN, but my input images are not labeled and I don't know how to do that automaticaly I mean not manually, anyone can help me please ?
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Average loss is 0 when training dataset with darknet yolov4
I am currently training a dataset using yolov4 darknet from AlexeyAB Github found here:
https://github.com/AlexeyAB/darknet
The dataset I am training is called FishNet Open Images. The dataset has 86,...
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How to prepare training data for deep learning models
I am working on a project which involves the application of deep learning models. I have collected training data. In collected images, I have more than one object in interest. I am not very clear how ...
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Problems finding an LSTM model for classification
I am doing a study for the classification of musical genres using deep learning techniques. The work consists of making a classification using an LSTM model.
I am using GTZAN as a data set, and ...
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Is it possible to solve Rubik's cube using DQN?
I'm trying to solve Rubik's cube using deep learning and I came across with DQN, so I decided to give it a try. I developed all the code and started training but I got this results:
Loss goes up and ...
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Which is better: multi-output model or separate models for similar tasks?
I am working on two problems:
classification of images into high-level classes (e.g. shoe, dress, jacket etc.)
classification of the attributes of the same images on a lower level (e.g. shoe style, ...
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How is attention different from linear MLPs?
Each output for both the attention layer (as in transformers) and MLPs or feedforward layer(linear-activation) are weighted sums of previous layer. So how they are different?
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Anomaly detection for time series data with only positive samples?
I'm having a time series ECG dataset. I want to do anomaly detection (anything different from normal ECG should be abnormal).
The point is I'm having only positive samples with very few negative ...
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Evaluation of semantic segmentation network with mAP
I am interested in evaluating a semantic segmentation network. I've seen lots of challenges such as PASCAL VOC use the mean average precision metric(mAP). I understand how this would work with an ...
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Is reinforcement learning suitable for the Dial-a-Ride problem?
Is reinforcement learning suitable for this problem or will it perform poorly against classical algorithms?
"The Dial-a-Ride Problem (DARP) consists of designing vehicle routes and schedules for ...
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What are the equations involved in calculation of the parameters of embedding layer?
I'm trying to perform sentiment analysis on some data using keras.I'm using embedding layer and then LSTM. I know that embedding layer decreases the sparsity of the one hot encodings of the words and ...
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BPTT vs Vanishing Gradient Problem
I know that BPTT is the method to apply Back Propagation on RNN.
Which is works fine with RNN as it stops at certain point as changes approach to zero
but isn't it the exact Vanishing Gradient ...
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Structuring CIFAR100 for resnet18
This will probably be a basic question since I am starting with computer vision. I am trying to use resnet18 from pytorch and work with CIFAR-100 dataset. Single image has size 3x32x32 and the model ...
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The channel dimension of the inputs should be defined. Found `None`
Hello I'm trying to use SegNet in my project with tensorflow, for educational purpose. And I'm surely following someone else's code on GitHub:
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Metrics values are equal while training and testing a model
I'm working on a neural network model with python using Keras with TensorFlow backend. Dataset contains two sequences with a result which can be 1 or 0 and positives to negatives ratio in dataset is 1 ...
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CNN with Multi channel input or CNN with Multi instance learning?
I have 500 Dicom images of medical scan of patients. These are 3 dimension scans , shape = [300 x 300 x 3]. From these I have extracted Front and side views. So, for each patient I have 2 images of ...
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Using cropped background images as background class
I’m currently working on a binary image classification problem using high resolution (up to 6000x4000 pixels) images with complex backgrounds, and CNN transfer learning.
In order to reduce Images size ...
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How do I interpret GRAD-CAM's feature attribution to time series zero-padding in a CNN classifier?
Problem setting: MTS Classification with CNN architecture
I have a multivariate time series (MTS) dataset that contains 30 features. The goal is to solve a classification problem on this MTS dataset. ...
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Is a dense layer required for implementing Bahdanau attention?
I saw that everyone adds Dense( ) layer in their custom Bahdanau attention layer, which I think isn't needed.
This is an image from a tutorial here. Here, we are just multiplying 2 vectors and then ...
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What is the best approach to perform information extraction from tourist reviews using NLP, DL?
I am interested in performing some information extraction from tourist reviews about different places.
I have data of 50 different places and around 300-400 reviews about each of them and I would like ...
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``Hierarchial features extraction'' in Multilayer Perceptron models
I am referring to plain neural networks, MLPs.
I got to read the paper by Glorot and Bengio (2010), Understanding the difficulty of training deep feedforward neural networks.
Therein I read an ...
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How to serve deep learning model using tensorflow lite
I am trying to serve an image caption model based on flickr8k dataset using TensorFlow lite in the android app.
I am new to Android App development and stuck at the below code where I need to provide ...
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How to Use Multiple Adapters with a Pretrained Model in Hugging Face Transformers for Inference?
I have a pretrained Llama-2 model in the models_hf directory and two fine-tuned adapters: a summarization adapter in ...
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Tensorflow keras fit - accuracy and loss both increasing drastically
ubuntu - 20.04
tensorflow 2.2
dataset used = MNIST
I am testing tensorflow and i notice that validation sparse_categorical_accuracy (accuracy) and validation <...
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Feedforward Deep neural network
Is there anyone capable of converting this diagram? Please see the image description provided.
Similar to this
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How does a CBoW model convert a word to a vector?
A CBOW model actually takes multiple words as inputs and a targeted central word as the output.
So, the trained model actually maps several words to a single one, I mean it takes context words and ...
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How to detect the begin word and end word in a sentence with machine learning
I have some English text that has been tokenized. For example, the length of text token is about 20000 and each word (tokenize) has an index. Also, each index has a label, as the beginning word in a ...
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Feedforward Deep neural networks
Hello everyone can you help me to create a diagram for these F-DNN
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Calculating saliency maps for text classification
I'm following the text classification with movie reviews TensorFlow tutorial, and wanted to extend the project by looking, for a certain input, which words influenced the classification the most.
I ...
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How high of a correlation coefficient of a feature with a target variable is considered too high?
Currently my classification model is doing too well on all of the train, validation, and test datasets. I'm assuming there is a data leakage in the features, and therefore I've computed the ...
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how to link the predicted output to the original observation?
Am working on a binary classification using logistic regression data
I have 1000 rows and 28 features. Three to 4 variables are Id variables like product_id, subject_id etc
During train_test split, I ...
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activation=tf.keras.activations.relu vs activation='relu'
Both models are for binary classification problems
Model 1
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What is the function of the hidden layer in a neural network mapping to?
The hidden layers of the neural network which are in between the input layer and the output layer take in input data and apply a function to churn out data from each node which is then weighed by the ...
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Confusion with tensorflow's Sequential Dense Layers
I'm working on a regression probem using Tensorflow, and have created two models with slight differences in their first Dense layer.
The Models
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How can I generate handwritten notes given any handwriting sample and text file?
I am new to ML/DL and looking for a good way to generate a handwritten (simulated) file given 2 inputs:
A set of sample handwritten notes (for training). All notes will be from the same person.
A ...
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Keras multi GPU in vast.ai
I am trying to run a keras model on vast.ai using multiple GPUs. For that I am using keras.utils.multi_gpu_model , however I keep having this error:
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How to run two different models in single frame?
I have mask_detector.model and yolov3 social distancing weights.
I want to run them simultaneously with a single webcam stream.
how can I run them both i.e. detecting mask and social distancing model ...
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Is there a relationship between learning rate and training set size?
I have a large dataset to use for training a Neural Network model. However, I don't have enough resources to do a proper hyperparameters tuning on the whole dataset. Therefore, my idea is to tune the ...
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[Keras][LSTM] error due to shape mismatch
I have following data. Where I have 2 samples. Each sample I have 3 time steps each with 2 features. I intend to have 2 batches (to updates weights after every sample)
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Problems with Concatenating Embedded Categorical and Numerical variables for LSTM use
I am new to here and new to Deep Learning too, so apologies in advance for any ill formatted code or wordings. I have a data set where I track 4 variables with 2 categorical and 3 numerical fields, ...
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Explanation of why Neural Networks are non convex
Why having a symmetry of values for the hidden state imply that the neural network is non convex? I could not find an intuitive answer for this yet.
Also, if we consider a Fully Connected network wtih ...
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Measuring Product Search effectiveness
I want to measure the effectiveness of my search engine, one of the ways i can do that is by measuring the rate at which a customer reformulates the previous query. Hence, I need to quantify inter-...
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How was the word2vec model trained?
Let's take the CBOW (continuous bag of words) model as the example.
Suppose that, there are $c$ context words, each of which is a one-hot encoding vector. So the total number of elements of input ...
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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 ...
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How to use text as an input for a neural network - regression problem? How many likes/claps an article will get
I am trying to predict the number of likes an article or a post will get using a NN.
I have a dataframe with ~70,000 rows and 2 columns: "text" (predictor - strings of text) and "likes&...
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Aspect-Based Sentiment Analysis with Bert and Pytorch
I have a dataset of online reviews (X) with their corresponding topics (topic1 to topic5) and each topic can have 5 values (fined-grained sentiment score from 1 to 5). So, I have one X and 5 Y columns....
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