Questions tagged [keras]
For questions related to Keras, the modular neural networks library written in Python. However, note that programming questions are off-topic here.
256
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kerascv retinanet for gender identification
I am using KerasCV Retinanet to detect people and their genders in images.
I would like to detect "man", "woman", "boy", "girl" and "baby" in images. ...
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I'm trying to build image search like Google Photo-Image with face is given to model & it'll get all the images in database in which he/she is present
When a user upload a selfie, the model search same person in dataset of images of multiple persons and get back all the images in which that person is present.
Step 1: From dataset of images I detect ...
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Transfer learning using pretrained tensorflow object detection model [closed]
I am new to AI/ML and wanted to seek guidance as I am totally lost. I will simplify my issue as follows:
Let's say I would like to detect apples and oranges in images.
I would like to leverage a pre-...
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How is the accuracy as a metric in a Keras machine learning model calculated? Is it a valuable metric for LSTM
I'm training a LSTM neural network for time series prediction in Keras. During the training of the model, the loss (mse) gradually decreases each epoch, but the accuracy as well as the validation ...
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Must I "prime" my normalizer with the same data I trained it with in order to use it?
I trained a Keras Network. During training, I would first initialize a normalizer from the values in the entire dataset, then partition into train, test and validation datasets. After partitioning, I ...
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MultiLayer Perceptron not working for regression problem, what could I try?
I am trying to learn the inverse kinematics of a robotic manipulator. To do that I have a simulator with which I acquired data.
My dataset is composed of positions in X, Y and Z and actuator variables ...
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41
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How to setup correctly a sequence generation task with RL/policy gradient learning?
I've a pretrained model for sequence generation that I'd like to improve with RL but there are several shady points.
So, I have the following model and loss function:
...
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Easiest way to train a neural-network with neurons that deviate from $f_{nl}(x \cdot A)$
I want to model how a neural network would behave for a system of input-output devices that are only approximately similar to a neuron. I think I have a resonable plan for how to do this, but I'm ...
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Updating custom output layers of an LSTM network
I have a text generation task learning to predict the next word with an LSTM network with multiple output layers.
After the generation of a sentence has finished, I calculate a reward for the whole ...
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good period prediction but bad magnitude using keras LSTM neural network
I want to predict the voltage of a battery along time using neural networks. This voltage is read using an ADC and generates a charge/discharge profile that ideally looks like this:
Which goes very ...
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Incorporating HiPlot and Keras
I just started to learn about Keras and train some models, and I came across HiPlot which is used for tuning hyperparameters. I was wondering if HiPlot can also be used to see what parameters would ...
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Tips for getting LSTM to train for next word predcition
I am trying to train an LSTM network for next work prediction. I have scraped a rather large dataset from Wikipedia of country descriptions. I have done normal preprocessing (removing punctuation and ...
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How can an MLP be implemented with convolutional layers?
I am studying the architecture of the network pointnet, specifically the MLPs stages of the pipeline highlighted in red in the following image (taken from the author page here):
It is strange to find ...
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How can I tell a CNN to ignore nodata values in satellite images?
I'm trying to train an image segmentation model on satellite images. There are two main issues: first, not all of the images are the same size. My understanding is that by using a fully convolutional ...
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735
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Keras Subclassing : TypeError: 'KerasTensor' object is not callable Call arguments received by layer [closed]
Implementing UNet but getting an error: type error 'KerasTensor' object is not callable
...
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Regression Model diverging after adding a new feature with higher variance and magnitude
In a time series regression problem I'm predicting "change" rather than the actual intended value i.e
Instead of:
...
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29
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How to use UPSNet or Mask-RCNN? How to format image data for panoptic segmentation?
I want to use UPSNet (github repo) (paper) to train a model to perform panoptic segmentation on my own dataset. I would also consider using a model based on Mask-RCNN to simply perform instance ...
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17
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Hard time trying to fix overfit
I'm trying to make a binary classification model using keras, but it seems to overfit every time. I have tried differents architectures and its seems that a larger model performs better than a smaller ...
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126
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Why do training and fixing a reservoir yield very similar results (in an echo state network)?
Disclaimer: I asked this question 2 days ago in Cross Validated, but it has been left unanswered.
I am trying to better understand how echo state networks work. To see, how fixing the weights of the ...
user68128
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61
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Best methods to square rectangular images for OR
I've read previous posts that assert using one of these solutions:
crop and or resize
nn input size independent
In my case, I am using some tensorflow models and afaik they report a fixed size like ...
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56
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How to setup a reinforcement learning model that changes the values of $x$ to maximize $y$ in $y = f(x)$?
Assuming a relation such that $y = f(x)$, where $y$ represents a scalar and $x \in 20 \times 1$ vector consisting of zeros and ones, I want to set up a reinforcement learning model that changes the ...
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Why is a simple regression problem so hard for an MLP to learn?
Consider a very simple problem, which is to find the maximum value out of a list of 5 numbers between 0 and 1. This is obviously trivial, but serves as a good example for a real-world problem I'm ...
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Found input variables with inconsistent numbers of samples
I have an issue. the model gave me an error of Found input variables with inconsistent numbers of samples: But I don't understand why
...
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Which type of neural network to use to classify data by which equation most likely generated it?
Problem Summary: Identify which equation a set of data was most likely generated from
Problem Description: Let's say I have two different equations that are functions of variables X and Y and ...
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How do I use ResNet for text processing?
I need to implement a deep neural network [residual neural network (ResNet)] that takes some text as an input [length M x N] and then processes it. Now as far as my understanding goes, ResNet is used ...
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125
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Why use z_mean to plot the latent space learned by a Variational Autoencoder?
In the Keras website, there is an example code of a Variational Autoencoder.
At the end of such a page, there is an example code that plots the latent space learned from MNIST. The code is as follows:
...
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Are there techniques (pygad - tpot-optuna)for best Genatic algorithm optimize hyper prameter cnn 1D
Iam new in mashin learning and i try to optimize tenser flow with keras conv1d model to improve classification by improve hyper kernal and filter
For training dataset csv =(1325,33,1) with outputs ...
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Referencing features by name instead of index when feeding inputs
Traditionally the inputs of a model is a matrix of N dimensions.
This works well with inputs that are position-sensitive (For example in CV the placement of the pixels relative to each other can be ...
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Are the "artifacts" in select Keras MNIST training images really there or is my download corrupt?
I'm having fun with a ludicrously well known and used dataset: mnist.
I am doing it with a huge and well known tool: keras.
Please excuse the red dots, something else I was doing. I have otherwise ...
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agent based DNN with a loopback
I have a data problem with no direct reward mechanism,(test/train) good and fault solutions.
Though over a long time period good decisions might be made.
I've been searching for days now for an agent ...
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How embeddings learned from one model can be used in another?
In the website the following explanation is provided about Embedding layer:
The Embedding layer is initialized with random weights and will learn
an embedding for all of the words in the training ...
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Loss Function for Binary Classification with Multiple Correct Choices
I have a binary classification problem, where there are multiple correct predictions, however, I would consider the prediction to be correct if the highest confidence prediction of a 1 is correct.
I ...
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What data can I obtain from CNN model (H5 file)? [closed]
I created a CNN model and it is saved in h5 format. I used the Netron app, where I obtained the model architecture, however ...
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Help on Deep Sarsa algorithm that work with pytorch (Adam optimiser) but not with keras/Tensorflow (Adam optimiser)
I have a deep sarsa algorithm wich work great on Pytorch on lunar-lander-v2 and I would use with Keras/Tensorflow. It use mini-batch of size 64 wich are used 128 time to train at each episode.
There ...
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keras model accuracy not improving
I am trying to do multi class(16) classification, however no matter what parameters or number of layers I use my accuracy is not improving, its in 30s the max I got was 43.
I have tried early stopping ...
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Why does my neural network perform different on the same images during training and testing?
I use tensorflow keras to build a neural network that classifies images of covid-19 rapid tests into three classes (Negative, Positive, Empty).
During training the ...
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How exactly does Keras calculate the validation accuracy?
After each epoch, Keras provides the following evaluations (depending on how the model is compiled):
train_accuracy
train_loss
validation_loss
validation_accuracy
Keras evaluates the performance of ...
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Shuffling vs Non-shuffling train/test set yields drastically different results
I am currently working with a very deep NN (200mio. to 350mio. params). My data set is roughly of shape (2mio, 350), i.e. 2mio samples and 350 features. In fact, the features are time series. As input ...
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Time taken to solve cartpole environment using DQN
I am trying to solve the cartpole environment (GitHub) using DQN agent. I have been building my own DQN agent by following a tutorial by Jon Krohn.
I am able to solve the environment with a maximum ...
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267
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Why can't I reproduce my results in keras using random seed? [closed]
I was doing a task using RNN to predict a time series movement.
I want to make my results reproducible. So I strictly followed this post:
https://stackoverflow.com/questions/32419510/how-to-get-...
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225
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Is it possible to learn the number of layers?
Is it possible, in a transformer or other deep architecture, to include the number of layers as a parameter of the model so it could be learned?
In fact, I have a keras layer that I use to change the ...
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Denoise autoencoder not training properly [closed]
I'm trying to make a denoise autoencoder wherein the encoder part is vgg16 and decoder is opposite of vgg16(encoder) network. My dataset consists of 5K images in grayscale.
Now while training, the ...
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can't find a viable import class for keras.utils.Sequence [closed]
I am using Google Colab. tensorflow version = 2.8.0, and keras is the same. I am trying to get a BalancedDataGenerator(Sequence) class created, but I can't get <...
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96
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Overfitting problem - poor performance on test data
I'm facing the problem of overfitting and I can't deal with it - I tried experimenting with optimizer, but nothing seems appropriate. My model has extremely poor performance on testing data and the ...
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596
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Do the values over 0.5 mean my model classified the data as a "1" label and vice versa?
I am doing binary classification using an LSTM and my output layer is 1 neuron with a sigmoid function. My labels are either 0 or 1.
...
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715
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Which approach can I use to generate forged signatures from real ones?
I am in internship period and I'm working on a signature verification problem.
This process needs real and forged signatures. All I have are the real signatures (like 30 signatures per person), and I ...
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1
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208
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Where can I find authentic references on "categorical cross entropy" and "categorical accuracy metric"?
My Python source code uses TensorFlow and Keras to implement a neural network.
The Keras source code uses something called "categorical cross-entropy" and "categorical accuracy metric&...
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887
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Low accuracy and high loss in multi-class classification [closed]
I'm trying to classify images in 17 flowers dataset which consist of 1360 images of 17 classes (80 images per class); I have to use DNNs only therefore I made my model with the following settings:
<...
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516
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Weights initialization once the Neural Network is trained
I am trying to understand how weights are initialized in a Neural Network using Keras deep learning framework and what happens if I train a Neural Network and then I want to train it again: are the ...
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102
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Why does validation accuracy stop rising so soon?
I have implemented a GRU to deal with youtube comment data. I am a bit confused about why the validation score seems to even out around 70% and then keeps rising, this doesn't look like overfitting ...
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