TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset

Neural network (CNN) with TensorFlow [AlexNet architecture] that classifies 4 types of geometric shapes. Validation accuracy ~ 99.3% so nothing impressive here.

cifar, imagenet

This repository contains classification of Intel image dataset with numerous algorithms. Enjoy 🙂

AlexNet Implementation in PyTorch

This repository is a comprehensive exploration of image classification methodologies using CNN architecture, such as a dynamic Residual CNN and AlexNet model. Through PyTorch implementation, hyperparameter tuning, and detailed training scripts, the repository emphasizes robust image classification techniques with a focus on diverse scenes.

Convolutional Neural Net implementation using pytorch for CS7GV1

Implementation of different CNN architectures

Feature extraction network using AlexNet and TensorFlow to use on the German Traffic Sign Recognition Benchmark dataset

Implementation of AlexNet through a Transfer Learning Approach over CIFAR-10 Dataset using PyTorch from Scratch, presenting an accuracy of ~87%

밑바닥에서 부터 시작하는 딥러닝

Dogs Image Classifier classifies pet images to dogs and not dogs and identify the breeds of the classified dogs using transfer learning via PyTorch pretrained models.

🥸✅ 🐵❌Developing a babysitting algorithm to preprocess CIFAR10 and FDDB Dataset and train them on Alexnet using Pytorch

In this repo, I implemented VGGNet, MobileNet and AlexNet and compared their performance on Emotion Detection Task using AffectNet dataset.

An image recognition project to detect all sunset/sunrise images with machine learning and SVM in 5000+ images.

implementation of some ml algorithms

Assignments of Machine Learning course

Implementation of VGG and Alexnet for image classification of dogs and cats. Also modify the network for a faster training on this task.