VGG16: A Deep Convolutional Neural Network for Image Recognition
VGG16 Theory
Advantages of VGG16
VGG16, proposed by Simonyan and Zisserman, introduced several key innovations:
Small Convolutional Kernels: It primarily uses 3x3 convolutional kernels instead of larger ones like 7x7. This approach offers two main benefits:
It reduces the number of parameters in the model.
It increases the model's non-lineari ...
Posted on Thu, 02 Jul 2026 16:10:49 +0000 by nick1
Comparative Analysis of Adam and SGD Optimizers in Image Classification
Environment and Hardware Configuration
To ensure efficient computation, the environment is configured to utilize available GPU resources dynamically. Non-critical warnings are suppressed to maintain a clean log output.
import os
import pathlib
import warnings
import tensorflow as tf
import matplotlib.pyplot as plt
# Configure GPU memory growth ...
Posted on Tue, 12 May 2026 21:41:58 +0000 by Tagette