About Binary Classification of Image Data using VGG models and their comparison and visualization on TensorBoard

Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources

In this tutorial, you will discover the VGG convolutional neural network models for image classification. After completing this tutorial, you will know: About the ImageNet dataset and …

This code uses VGG16 for binary classification of images.""" import numpy as np import tensorflow as tf from tensorflow.keras.applications import VGG16 from …

Aug 1, 2021 · I have been trying to create a confusion matrix to test my data on from my VGG16 classification model (python 3.8, using Keras). I found a boiler plate based off of …

vgg_arch=VGG16(input_shape=(img_width,img_height,3),weights="imagenet",include_top=False)

This is an implementation of image classification using cnn with vgg16 as backbone on Python 3, Keras, and TensorFlow. The model generates pattern to image classification. Dataset (Gdrive) …

Apr 4, 2025 · Implement pre-trained models for image classification (VGG-16, Inception, ResNet50, EfficientNet) with data augmentation and model training.

In this project, I applied convolutional neural network for image classification. And the end, I also applied VGG-16 convolutional neural network by using transfer learning.

Aug 25, 2024 · In this blog, we'll explore how to use Keras' built-in VGG models, focusing on how to load, modify, and apply them to image classification tasks.