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Questions tagged [keras]
Keras is a neural network library providing a high-level API in Python and R. Use this tag for questions relating to how to use this API. Please also include the tag for the language/backend ([python], [r], [tensorflow], [theano], [cntk]) that you are using. If you are using tensorflow's built-in keras, use the [tf.keras] tag.
I use CNN-LSTM model to predict whether system anomaly happened. The dataset is labeled system logs. The labels are log sequence based. Assume that every log sequence has 25 logs and every log has 15 ...
I am trying to create a Keras model with multiple inputs.
input_img = Input(shape=(728,))
input_1 = Input(shape=(1,))
input_2 = Input(shape=(1,))
x = (Dense(48,kernel_initializer='normal',...
New to ML and TensorFlow in general. Im getting this issue when I try to run this line (t_loss = loss_object(labels, predictions)) in the train_step function.
I feel i'm missing something super ...
I'm working on a custom Convolutional layer for keras, but part of what I'm trying to do involves modifying filters from within the layer. How would I access convolutions from within the convolutional ...
import keras.backend as K
from keras.optimizers import Adam
from keras.losses import binary_crossentropy
## intersection over union
def IoU(y_true, y_pred, eps=1e-6):
#print(y_true)
if np.max(...
I am trying to create a confusion matrix from classification. Y_pred_one_hot.shape and Y_true_one_hot.shape return (11,13) and y_pred and y_true return a list of 13 integers. However, I get the error ...
I am trying to convert a function generator I wrote for keras because I would like to use more than one of my cpus processor to speed up the training process and keras does not allow me to simply ...
I have a list of images along with the class it belongs to in this format:
list.txt
image1 good
image2 good
image3 good
.
.
.
image4 bad
image5 bad
image6 bad
I used the ImageDataGenerator to split ...
I am trying to predict 4 variables, but what I really care about is the sum of the variables over what any particular variable is. With that in mind, I've defined my model like:
import keras.backend ...
Briefly, I put in place a data input pipline using tensorflow Dataset API. Then, I implemented a CNN model for classification using keras, which i converted to an estimator. I feeded my estimator ...
I have implemented an emotion detection analysis using lstm, I have firstly trained my model with a dataset of reviews and its emotion, then I have implemented the predicting part where I have put my ...
This is my model, and I have implemented it once in TensorFlow.
def create_compiled_keras_model():
inputs = Input(shape=(7, 20, 1))
l0_c = Conv2D(32, kernel_size=(7, 7), padding='valid', ...
I am using google colab. While using EfficientNetB3 i am getting the following error
Resource exhausted: OOM when allocating tensor with shape[15,95,95,192] and type float
I understand this because ...
import keras
import numpy as np
from keras.applications.vgg19 import VGG19,preprocess_input
from keras.preprocessing.image import img_to_array,load_img
from keras import models, layers, Model
from ...
Tell me how you can implement the CNN neural network so that it helps to recognize the background of the object, and against the background I need the figure. That is, I have two textures - wood and ...