Could you help me with the code such that along with the dense layers also the last convolutional layer of Efficientnet is trained as well ? features_url ="http
I have a keras model trained for occupancy detection of parking spaces, which I load using keras.models.load_model(PATH_TO_MODEL). The input for the model is a
I've tried to run a code example (hosted on keras.io) regarding the handwriting recognition task. While playing with the code, I faced a TensorFlow-related issu
I'm implementing a UNet neural network but I'm having some issues while importing libraries. I found a solution for a couple of them, but I still have a problem
I have a very large file and I want to divide it into smaller ones for training. I've read about pickle files, so I split the large file into training-validatio
I want to train a model with self-generated matrices (word vectors). My data have the following datatypes: print(type(X)) print(type(X[0])) print(type(X[0][0]))
I am a beginner learning deep learning by Keras. The ImageDataGenerator class in Keras and the flow_from_directory function made it easy to label images. But al
I'm trying to improve my val accuracy as it is very low. I have tried changing the batch_size, the number of images being used for validation and training. Adde
I am getting the following error message when trying to run this AlexNET python code. Traceback (most recent call last): File "C:\Users\PycharmProjects\Local-
I trained my model with frozen backbone like: model.get_layer('efficientnet-b0').trainable = False Now, I unfreeze backbone, compile model, start training and
I am looking for a solution for a problem that has arisen when building a generic ANN for image classification in R. What I want to do is either: Design and com
I want to build an MLP classifier on iris dataset. Actually, I want to build a function that runs the model with N hidden units in the hidden layer and a loop t
Keras documentation about fine-tuning states that it is important to "keep the BatchNormalization layers in inference mode by passing training=False when callin
I am working on image classification using CNN. I am using below source code for that task. I am stuck with this error : AttributeError: 'NoneType' object has
from matplotlib import units import numpy as np from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense from tensorflow.keras
I try to find a proper solution to convert a rgb mask from "cam vid" dataset to categorical mask. I have the list of rgb value and corresponding label. What is
I am trying to train a model based on the U-Net architecture. I am using two data generators (one for training, the other one for validation). However, whatever
I am training convolutional autoencoder and I have this code for loading data (images): train_ds = tf.keras.preprocessing.image_dataset_from_directory( 'pat
I am trying to write a custom metric in keras like this: def C_index1(E,T): T = T.reshape(len(T),1) T_ind = T > T.T E_ind = E.reshape(len(E),1) E_ind
I'm a beginner of data-science and by now, I'm trying to migrate old code keras cpu modelling to gpu-tensorflow. fyi: I'm following instruction on prof.jeffheat
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