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Questions tagged [vgg16]

Use for questions about VGG16, the Convolutional Neural Network (CNN) model developed by researchers at the University of Oxford.

VGG16 is Convolutional Neural Network (CNN) model developed by researchers at the University of Oxford and (at present) attains cutting edge results when applied to the ImageNet dataset. The architecture relies on a series of convolutions + RELU, max pooling, fully connected layers + RELU, and a soft max layer at the end.

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Is Faster RCNN the same thing as VGG-16, RESNET-50, etc... or not?

My understanding is that Faster RCNN is an architecture for performing object detection. It finds objects in an image and classifies them. My understanding is also that VGG-16, RESNET-50, etc... also find objects in images and classify them. Are…
b19wh33l5
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Why is input preprocessing in VGG16 in Keras not 1/255.0

I am just trying to use pre-trained vgg16 to make prediction in Keras like this. from scipy import ndimage from keras.preprocessing import image from keras.applications.vgg16 import preprocess_input im =…
kawingkelvin
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vgg16 needs less epochs than resnet ,why?

Recently i Have been comparing the vgg16 with resnetv1 with 20 layers.I have found out that although each epoch on vgg takes more time to complete,it generally needs less epoch to reach a certain training accuracy than resnet20.Why vgg learns faster…
Moeinh77
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How to combine different models in Keras?

I have a pre-trained network, consist of two parts, the feature extraction, and the similarity learning. The network takes two inputs and predicts the images are same or not. The feature extraction part was VGGNet 16 with all layers freezed. I only…
Ali Raza Memon
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How to fine tuning VGG16 with my own layers

I want to maintain the first 4 layers of vgg 16 and add the last layer. I have this example: vgg16_model = VGG16(weights="imagenet", include_top=True) # (2) remove the top layer base_model = Model(input=vgg16_model.input, …
0nroth1
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Why are my predictions bad, if my accuracy in train is roughly 100% (Keras CNN)

In my CNN i have to handle 2 classes in a binary system, I have 700 images each class to train, and others to validation. This is my train.py: #import tensorflow as tf import cv2 import os import numpy as np from keras.layers.core import Flatten,…
user84391
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Neural Network Model using Transfer Learning not learning

I am a beginner in Deep Learning and working on Road Crack detection using transfer learning. I am working on binary classification with two classes , crack and no crack. My distribution of two classes is as follows: Cracks - 600 images No cracks -…
Shreya
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How to calculate $\phi_{i,j}$ in VGG19 network?

In the paper Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network by Christian Ledig et al., the distance between images (used in the loss function) is calculated from feature maps $\phi_{i,j}$ extracted from the…
Nagabhushan S N
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Overfitting in CNN

I am training a VGG net on STL-10 dataset I am getting Top-5 validation accuracy about 98% and Top-1 validation accuracy about 83% But both the Top-1 and Top-5 Training accuracy is reaching 100% Does this mean that the network is over-fitting? Or…
Siladittya
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Is this an over-fitting case?

I'm a new programmer and this is my first ever neural network for real world application. Here is the deal, I'm using a top-less pre-trained VGG-16 with some dense layers on top of it.(for image classification problem) But no matter what hyper…
kaboo
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Why is convnet transfer learning taking so long?

I am using transfer learning to train a binary image classification model using keras' pretrained VGG16 model. The code can be found below : training_dir = '/Users/rishabh/Desktop/CyberBoxer/data/train' validation_dir =…
Rishabh Sharma
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How to find which patch in orignal image does an activation correspond to in vgg net after the final pooling layer

So I am working on the NeurIPS 2019 reproducibility challenge, The link to the paper is https://arxiv.org/abs/1806.10574. So basically we have a vgg-16 net with the final fully-connected layers removed, so we get the 7x7x512 dimensional activation…
AYUSH MANGAL
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How to increase the accuracy of my predictions (CNN fine tuning VGG16 KERAS)

In my VGG16 fine-tuning, I have to classify retinal images in 2 classes (or 4th stage or not 4th stage) and I have 700 images each class to train. This is my code now: TRAIN_DIR = 'train/' TEST_DIR = 'test/' v = 'v/' BATCH_SIZE = 32 NUM_EPOCHS =…
0nroth1
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Using the first 3 layers of a pretrained network in Keras

I want to use the 3rd layer's output of the VGG16 network. The error is like below: UserWarning: Model inputs must come from `keras.layers.Input` (thus holding past layer metadata), they cannot be the output of a previous non-Input layer. Here, a…
Anil
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Shared classifier for 3 neural networks (is this weights sharing?)

I would like to create 3 different VGGs with a shared classifier. Basically, each of these architectures has only the convolutions, and then I combine all the nets, with a classifier. For a better explanation, let’s see this image: I have no idea…
CasellaJr
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