Questions tagged [keras]

For questions related to Keras, the modular neural networks library written in Python

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14 views

Keras model accuracy not improving beyond threshold

I am currently working on a public project for the National Weather Model. We are experimenting with using a recurrent neural network to replace the output of a quadratic formula that is in use. The ...
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1answer
56 views

Understand the DDPG algorithm in Keras

I'm trying to understand the DDPG algorithm using Keras I found the site and started analyzing the code, I can't understand 2 things. The algorithm used to write the code presented on the page In the ...
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2answers
40 views

Is there a neural network that accepts both the current input and previous output?

I am quite new to neural networks. I am trying to implement in Python a neural network having only one hidden layer with $N$ neurons and $1$ output layer. The point is that I am analyzing time series ...
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1answer
72 views

Why is my validation/test accuracy higher than my training accuracy

Is this due to my dropout layers being disabled during evaluation? I'm classifying the CIFAR-10 dataset with a CNN using the Keras library. There are 50000 samples in the training set; I'm using a ...
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1answer
41 views

How can I use autoencoders to analyze patterns and classify them?

I generated a bunch of simulation data from a complex physical simulation that spits out patterns. I am trying to apply unsupervised learning to analyze the patterns and ideally classify them into ...
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1answer
101 views

Why is this ResNet50 misclassifying objects?

I'm new to Deep Learning, and I have some conceptual problems. I followed a simple tutorial here, and trained a model in Keras to do image classification on 10 classes of logos. I prepared 10 classes ...
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1answer
96 views

Which model can I use for this problem with multiple inputs and outputs?

Which model is the most appropriate for this problem with multiple inputs and outputs? The data set is A1, A2, A3, A4, A5, A6, B1, B2, B3, B4 where ...
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1answer
65 views

Is there a car detection software written in Tensorflow or Keras with Python?

For a current project demo, I'm searching for a car detection neural network in Python written in TF/Keras (or any other type, as long as it has no C++ dependencies). Later on, I gonna write my own, ...
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0answers
49 views

What is the best way to make a deep reinforcement learning environment with a continuous 2D action space?

I understand that the actor-critic method is probably where I want to start because of how it works with continuous action spaces. However, the problem I am trying to solve would require the action be ...
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0answers
46 views

ConvNet - What to improve regarding architecture, procedure and technique?

I have a dataset of 180k images of license plates (so, not necessary to localize the license plate at first) for which I try to recognize the characters on the images (License plate recognition). All ...
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1answer
86 views

Which is better to start deep learning and understand it in depth (and not just a simple overview) - pytorch or tensorflow 2.0?

I am beginning to learn deep learning. I recently spoke with an expert in the field. He suggested that I start with pytorch because of these reasons: Keras abstracts the stuff a lot that we will not ...
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0answers
45 views

Embedding Layer into Convolution Layer

I'm looking to encode PDF documents for deep learning such that an image representation of the PDF refers to word embeddings instead of graphic data So I've indexed a relatively small vocabulary (88 ...
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2answers
41 views

How can I have the same input and output shape in an auto-encoder?

I'm building a denoising autoencoder. I want to have the same input and output shape image. This is my architecture: ...
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1answer
32 views

Is CNN capable of extracting the descriptive statistics features

I was trying to build a CNN model. I used time series data of daily temperature to predict if there is risk of an event, say bacteria growth. I calculated the descriptive statistics of the time series,...
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6answers
9k views

Why do CNN's sometimes make highly confident mistakes, and how can one combat this problem?

I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I'm feeding in a bunch of handwritten digits, and non-digits from a document. I want the CNN to report errors, so I ...
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1answer
45 views

When would bias regularisation and activation regularisation be necessary?

For Keras on TensorFlow, a layer class constructor comes with these: kernel_regularizer=... bias_regularizer=... ...
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1answer
31 views

Number of LSTM layers needed to learn a certain number of sequences

Theoretically, number of units for a LSTM layer is the number of hidden states or the max length of sequences as per my practice. For example, in Keras: ...
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0answers
37 views

Micro average f1_score, None average f1_score cannot increase more than 0.71, 0.50 respectively for the best model estimator

I am training a multilabel text neural network and the model metric I chose, to measure the performance of the training and the validation sets, is the f1 score (Micro average, None average). However, ...
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0answers
34 views

CIFAR-10 can't get above 10% Accuracy with MobileNet, VGG16 and ResNet on Keras

I'm trying to train the most popular Models (mobileNet, VGG16, ResNet...) with the CIFAR10-dataset but the accuracy can't get above 9,9%. I want to do that with the completely model (include_top=True) ...
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1answer
40 views

Do correlations matter when building neural networks?

I am new to working with neural networks. However, I have built some linear regression models in the past. My question is, is it worth looking for features with a correlation to my target variable as ...
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0answers
38 views

Inaccurate masks with Mask-RCNN: Stairs effect and sudden stops

I've been using matterport's Mask R-CNN to train on a custom dataset. However, there seem to be some parameters that i failed to correctly define because on practically all of the images, the bottom ...
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2answers
1k views

Why would you implement the position-wise feed-forward network of the transformer with convolution layers?

The Transformer model introduced in "Attention is all you need" by Vaswani et al. incorporates a so-called position-wise feed-forward network (FFN): In addition to attention sub-layers, each of the ...
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1answer
43 views

Hand-Signs Recognition using Deep Learning Convolutional Neural Networks

I am developing a CNN model to recognize 24 hand-signs of American Sign Language. I have 2500 Images/hand-sign. The data split is: Training = 1250 Images/hand-sign Validation = 625 Images/hand-sign ...
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1answer
50 views

Binary mode or Multi-label mode is correct when using binary crossentropy and sigmoid output function on multi-label classification

I would like to ask a question about the relationship of accuracy with the loss function. My experiment is a multiclass text classification problem, and I have built a Keras neural network to tackle ...
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0answers
22 views

Time distributed word position prediction

I am facing the following problem. I need to create a model to predict the product groups from product title. For each word in sentence I need to predict position of a word marked as product. My ...
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0answers
22 views

Different result from k-cross validation model and Train-Validation-Test split model ? (AI fresher question)

I am starting to learn about Neural Network and I have come into one problem that I am still learning how to figure it out. I have a dataset with shape (105,96) (105 samples and 95 first column as ...
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0answers
35 views

Why is my DDPG agent (implemented in TensorFlow) not learning?

I am trying to implement a Reinforcement Learning algorithm called DDPG in TensorFlow 2.x on a custom gym environment. I am new to TF. So, I started with the DDPG TF 1.x implementation from pemami4911....
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0answers
23 views

CNN keras accuracy not improving

I am trying to duplicate and learn from example given on this website . With my little modification, I am trying to simple exchange color for example like red to orange in an image. The original ...
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0answers
34 views

Which loss function and evaluation metric should I use for a multiple output prediction problem?

I was running into a situation with a data set like this I have 4 events and and they might happen together in pairs. I want to use 3 features to predict the coupling between event. I am building a ...
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0answers
25 views

Binary classification to recognize blobs on pictures generates many false-positive results

I am training a NN for blobs vs non-blobs recognition. Blobs example: Non-blobs: Keras architecture is: ...
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0answers
24 views

How much data do we need for making a successful de-noising auto-encoder?

Is there a guide how much data do you need for making successful denoising model using autoencoders? Or the rule is, the more data, the better it is? I tried with small dataset 350 samples, to see ...
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4answers
1k views

How to reproduce neural network training with keras [closed]

I want to see the effects of changing some training parameters (batch size, learning rate, optimizer...) to the accuracy obtained. The problem is that with the same parameters I get significantlly ...
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1answer
27 views

How to use 'Canny/Watershed' algorithm's output as an input for Image Classification Model

I have a very silly problem in hand. I have implemented 2 methods which give me the mask to separate the objects from the background. What I get from one method is the object encapsulated in the red ...
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1answer
52 views

not sure if fine-tuned network is finely-tuned

I am practicing with Resnet50 fine tuning for binary classification task, here is my code snippet. ...
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1answer
197 views

What are the ways to calculate the error rate of a deep Convolutional Neural Network, when the network produces different results using the same data?

I am new to the object recognition community. Here I am asking about the broadly accepted ways to calculate the error rate of a deep CNN when the network produces different results using the same data....
2
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1answer
239 views

Should I apply ReLU to non negative output?

Suppose I want to predict the position of a sensor based on its reading. I can first predict the unit vector and predict the distance to be multiplied to this vector. And I know that distance will ...
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1answer
264 views

How can I reduce the GPU memory usage with large images?

I am trying to train a CNN-LSTM model. The size of my images is 640x640. I have a GTX 1080 ti 11GB. I am using Keras with the TensorFlow backend. Here is the model. ...
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1answer
70 views

How do you manage negative rewards in policy gradient reinforcement learning?

The same basic question here, but 3 years old and no definitive answer: Negative reward (penalty) in policy gradient reinforcement learning The question is, if I'm doing policy gradient in keras, ...
1
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1answer
33 views

Heavily mixing signal differentiation from Open Set of backgrounds via CNN

To whomever can help out, I appreciate it. I am currently attempting to detect a signal from background noise. The signal is pretty well known but the background has a lotttt of variability. I've ...
2
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1answer
270 views

How do I get multiple loss per sample in keras evaluate?

Usually, when I evaluate() a model, I would get a single loss that is already averaged over all samples. How do I get the loss per each sample and return all of them? E.g. if my dataset has 100 ...
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1answer
845 views

Simple Image Processing AI for Fire Detection

I have absolutely no experience with any kind of AI and really want to create this: A program that can train on a set of images to determine if an image is showing a fire flame or not (for fire ...
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1answer
68 views

How to handle extremely 'long' images?

After transforming timeseries into an image format, I get a width-height ratio of ~135. Typical image CNN applications involve either square or reasonably-rectangular proportions - whereas mine look ...
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0answers
19 views

How does multiple outputs added from intermediate layers of a keras functional model influence its learning behaviour / gradients?

let us assume I have a keras functional model with 2 inputs. My model has two branchs, each branch for each input. The model only uses dense layers. The first input is the data itself (feature vector ...
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1answer
107 views

How to train a LSTM model with multi dimensional data

I am trying to train my model using LTSM layer in Keras (python). I have some problems regarding the data representation and feeding it into the model. My data is 184 XY coodinates encoded as a numpy ...
5
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2answers
77 views

Two data classes for a convolutional neural network, can one have a LOT more images for training than the other?

I have two classes in the training set: one that has images with a feature and the other of images without that feature. Can there be a LOT more images with "no feature" so I can fit in all possible ...
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0answers
33 views

How to convert something to vectors

I wanted to create an encoder, which is the first part of an autoencoder. I do not want to build the whole autoencoder but rather wanted to test whether my mobile device can support running an encoder ...
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1answer
462 views

Periodic Pattern in Validation Loss Curve

I am currently trying to solve a regression problem using neural networks. I want to detect movement patterns in images over time (video) and output a continuous value. During the training process I ...
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1answer
44 views

Can we use a neural network that is trained using Reinforcement Learning for dynamic game level difficulty designing in realtime?

I am a newbie to Machine Learning and AI. As per my understanding, with the use of reinforcement learning (reward/punishment environment), we can train a neural network to play a game. I would like ...
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0answers
20 views

Keras word ordering task

I'm trying to solve the word ordering task: given a syntactically unordered sentence, recover the right order of the words. The adopted approach is to transform each sentence in a dependency tree and ...
1
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1answer
61 views

Why does this model have 12 parameters?

I guess the model shown in this image (img_1) is the same as the one in this image (img_2) I was trying to build a neural net like that. This keras code is to do the job. ...

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