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A Python library for machine learning, in particular for deep learning, originally created by Google.

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what are the ways to gain good accuracy in deep learning competition apart from changing hidden layer especially in case of image data set?

I am newbie in field of deep learning but i have experience in machine learning.like in machine learning competition we do plotting apply some statistics to gain understanding of data and by that we ...
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1answer
8 views

What are different methods to find the slow decrease in training/validation loss

I am training YOLO network consisting of resnet50 architecture.This problem is to find different text labels on the image and predict bounding boxes During training, I am seeing very less change in ...
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16 views

Help: training accuracy too low

[Using Keras/tensorflow] I'm trying to train a model suggested in this paper. I've set the weights of two convolutional layers as gabor filters. When I train the model, I'm getting the per wpoch ...
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4 views

Tensorflow dimensions /placeholders [migrated]

I want to run a neural network in tensorflow. I am trying to do email classification, so my training data is an array of count vectorized documents. Im trying to understand the dimensions for how I ...
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14 views

Computing average precision metric and cost fucntion for object detection task using scikitLearn and Tensorflow

I have a Data set that contains 5 thousand pictures of my object of interest and 5 thousand pictures with out it. I trained a Convolutional Neural Network using Tensor Flow to detect the position of ...
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21 views

When training a CNN, the validation loss and validation accuracy never changes. Is this a problem with the dataset?

When training a CNN, the validation loss and validation accuracy never changes. Is this a problem with the dataset? No matter what architecture or number of layers or set of parameters, the val train ...
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30 views

2-output node Neural network. Only the first output node can predict accurate enough results

I have a three hidden layer neural network. Input layer has 116 nodes(means I have 116 features in every training data set) and output layer has 2 nodes(means I have 2 labels in every training data ...
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21 views

How to build CNN to detect open defects? [closed]

I'm having enough dataset to train a CNN from scratch, but as I'm new to deep learning I'm confused that how I configure a CNN to detect open defects in image, because in dataset there are images with ...
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5 views

Best ML model for testing difference patterns in 1D arrays

I have a dataset where each row is a list of percentages per frame of an animation: ...
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1answer
32 views

Which algorithm for classification problem?

I want to create a ML (DL) model, that predicts the success of Facebook page-posts, based on historical data. My dataset represents a couple thousands posts, labeled 1 (successful) and 0 (...
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37 views

How to implement custom loss function on keras for VAE

I have implemented a custom loss function. While training the model, I want this loss function to be calculated per batch. ...
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0answers
34 views

Need help writing a neural network for a Pokemon battle

I'm trying to write a neural network that's able to select the optimal course of action in a Pokemon battle. In a battle, there are two different types of actions: use one of the four moves known by ...
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1answer
21 views

Uses of TensorBoard Projector besides word embedding?

I was wondering, are any examples of using the projector in TensorBoard for anything other than visualizing word embedding in natural language processing? It seems like a pretty general tool for ...
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1answer
32 views

Preparing test data for sentiment analysis in Tensor Flow

1) I want to do Sentiment Analysis using RNN + Tensor Flow + (Keras) 2) Is it necessary to prepare test data for sentiment analysis, using RNN, (or any Neural Network), in a certain format ? If so is ...
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6 views

Multiclass Sigmoid for DRL action picking

I am working on Deep reinforcement learning problem and I would like to use Sigmoid for my last layer instead of softmax. I am stuck on the what to use for action picking. Specifically, How should I ...
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47 views

Modeling a CNN to identify if image “is” or “isn't” something

I'm trying to build a CNN to play a game online. This game to be precise: https://www.gameeapp.com/game-bot/ibBTDViUP I've collected images and labels for each image. These labels tell the network ...
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1answer
19 views

Can a Fully Connected layer transform a 4D tensor to a 3D tensor by itself?

Recently, I was researching some topics in biometrics and I stumbled upon this paper. They have a table there (Table 1) in which they state that they used a modified CNN from this paper (Table 9). In ...
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1answer
36 views

What is the adventage of using Reinforcement learning in designing CNN?

I am looking at this paper Designing Neural Network Architectures using Reinforcement Learning. The paper discussed how to find the best network using ...
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1answer
81 views

Neural network regression: seemingly bounded output

I have been working on a neural network based predictor for a project. The aim is to learn a certain quantity, say the signal strength of a cellular network, for each coordinate set in the dataset. ...
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1answer
121 views

Improving spam classification with tensorflow logistic regression

I would like to classify a mail (spam = 1/ham = 0), using logistic regression. My implementation is similar to this implementation and using tensorflow. A mail is represented as a bag-of-words ...
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13 views

Decision tree / boosting tree in Tensorflow?

When I was looking for some way to break the bottleneck of memory limitation in xgboost, I found there are some boosting tree algorithm that is implemented in Tensorflow such as here. I have some ...
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19 views

Computation complexity and processing of one image for object detection in Convolutional Neural Network

How do I relate compute complexity in Convolutional Neural Network to processing time of one image in object detection for a given CPU/GPU's processing power? Say my CNN architecture needs ...
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1answer
56 views

Candidate Sampling for Softmax - Tensorflow; Sampling Probability

I am trying to understand the mathematics behind the sampled softmax in Tensorflow. They have the following document, trying to explain how the sampling process works: https://www.tensorflow.org/...
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1answer
27 views

Reduction of Feature map size in Convolutional Neural Network

In CNN, the way we reduce the feature map size at layers is we use pooling. Pooling makes feature map size into half. For the following network, if I want a new layer with feature map size somewhere ...
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18 views

Tensorflow Examples of Media Mixed Models

I'm starting to research MMM models and I was wondering if anyone knew of any examples of implementations in python with tensorflow. A github repo with some example code would be really handy for the ...
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2answers
76 views

Batch loss of objective function contains exp becomes nan

I am trying to solve a survival analysis problem, where all data are either left-censoring or right-censoring. I use an objective function which contains the CDF of Gumbel distribution. I have $m$ ...
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4answers
50 views

Difference between strided and non-strided convolution

conv = conv_2d (strides=) I want to know how non-strided convolution differs from strided i know how convolutions with strides work but don't know about the non-...
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1answer
35 views

Why is dropout causing my network to overfit so badly? [closed]

I've been experimenting with various simple neural networks to test their performance. When I use the following architecture, I'm getting some very bad test error, which looks like overfitting. $$\...
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28 views

Is it sensible for Dice Score to Reach its limit so early in training?

I am training a UNet for image segmentation purposes, using Dice Score as my loss function. I am using a 7-2-1 ratio for Train, Test and Validation set. My ...
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1answer
56 views

Epoch Vs Iteration in CNN training

There are a few discussions for Epoch Vs Iteration. Iteration is one time processing for forward and backward for a batch of images (say one batch is defined as 16, then 16 images are processed in ...
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12 views

What is the role of the large number of “Squeeze” nodes in a Keras NN graph (as presented by TensorBoard)?

I've built a relatively straight-forward network consisting of image and scalar input concatenated together after tiling the scalar with a Keras UpSampling2D layer. Then those concatenated layers are ...
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13 views

How should I choose the Encoder hyperparameters to make its memory state suitable for the Decoder in a Bidirectional Neural Network?

I'm trying to implement Neural Machine Translation following the tutorial on the Tensorflow website here https://www.tensorflow.org/versions/r1.8/tutorials/seq2seq and I was able to build a ...
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30 views

Do encoders/decoders preserve composition?

Let's assume that we have an encoder E and a decoder D implemented for instance as a Convolutional Encoder-Decoder, namely ED. Let's take two inputs X and Y, and some composition operator o operating ...
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1answer
29 views

Detecting mouse action with neural network

Inspired by sentdex Python plays GTA V series (https://github.com/Sentdex/pygta5), I decided to try some machine learning. Long story short - I made an app, which creates random red and blue filled ...
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1answer
104 views

what is the difference between binary cross entropy and categorical cross entropy? [duplicate]

So, I made a bidirectional LSTM model for sentiment classification. Model's job was to predict ratings of movies(1-5 stars) based on the movie review. While training the model I first used ...
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11 views

How to manually make predictions in tensorflow? (GANs)

So I have data (a bunch of vertices in 3d space), and I'm trying to generate similar shapes using a GAN in tensorflow. The results of the generator are near zero (so small you can't even see the shape)...
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9 views

Parameters to evaluate for the good accuracy of the network in CNN training

I have a few sets of CNN Network to train and I don't like to wait till the end of training for each network to evaluate, as it will take longer time. During the training I need to evaluate after a ...
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3answers
120 views

Tensorflow - Why do we need tensors? [duplicate]

Why do we need tensors in Tensorflow? I mean, if numpy can be used to create multidimensional arrays, which tensors essentially are, why do we bother creating ...
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1answer
34 views

What kind of neural network would solve classification of simple dataset [closed]

I decided to fit simple data, the rgb images of shape (w, h, 3) to cifar-10 neural network with 128 classes. For class number N I generated same images all filled with N value in all 3 channels. So, ...
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56 views

custom loss function to optimize payoff via binary decision

I have written a custom loss function that is supposed to optimize a payoff via a binary decision. However, the neural networks is struggling to convert, and I'm suspecting that there's something ...
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1answer
23 views

Output a value normalised to 1 over a number of groups from a neural network

Suppose I want to use a (deep) neural network to output a probability that is normalised to sum to 1 within each of a potentially arbitrary number of groups. For example, this might be something like ...
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51 views

Conditional GANs - conditioning scheme in TFGAN

In the 2014 paper on conditional GANs, https://arxiv.org/abs/1411.1784 the latent space vector z is augmented by a conditional variable, e.g. in the simplest case just the class label. There are ...
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1answer
42 views

which deep learning model to use for array sequence classification?

i am trying to classify a sequence of 10 numbers with keras and tensorflow. a common neural network doesn't seem to be an option. here is my data: ...
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1answer
140 views

Issue with Custom object detection using tensorflow when Training on a single type of object

I am training a pre built tensorflow based model for custom object detection. I want to detect only 1 type of object. I have taken lot of images from different angles and in different light conditions....
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1answer
23 views

Regularization in VGGNet-16 Network

I am looking into VGGNet. The networks are structured using Conv, Relu and Pooling layers only. How regularization is done in the VGGNet?
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26 views

How to solve a DC (Difference of Convex) program?

I have an objective function which is the difference of two convex functions in Tensorflow and I want to minimize it. Formally, I have the following problem: $\text{min}_{x \in \mathcal{X}} \;\;f(x)-...
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1answer
36 views

why the parameter 'scale' of tf.layers.batch_normalization is disabled when next layer is relu?

In the tensorflow documentation of tf.layers.batch_normalization,it is said" When the next layer is linear (also e.g. nn.relu), this(the parameter of 'scale' ) can be disabled since the scaling can be ...
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1answer
28 views

“Concurrent” LSTM network

Basically, my input can be thought of timeseries of timeseries (where each individual point of the timeseries is a timeseries as well - those subseries are all of the same length). You can interpret ...
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13 views

Number of Samples - Speaker Verification Model Evaluation - Precision-Recall-F1

When testing my Speaker Verification model, I am calculating Precision-Recall and F1 measure My test is as follow: This is considered as a binary classification problem. Either sample is from my ...