alexnet

Detect AI-generated images and photo edits offline using multi-dimensional analysis and error level detection in a Chrome extension.

🩻 Build a deep learning model for pneumonia detection in chest X-rays with a user-friendly web interface using TensorFlow and Streamlit.

This repository presents an innovative approach to classifying blood groups using fingerprint images through deep learning techniques. The project explores state-of-the-art convolutional neural network (CNN) architectures, such as ResNet, VGG16, AlexNet, and LeNet, to analyze and predict blood groups with the fingerprint images

Image classification for gingivitis screening using MobileNetV2 and AlexNet, with OpenCV-based preprocessing, Unsharp Masking, and external clinical validation.

Autonomous car using ESP32.

Part 2 of Visual Scrambling — AlexNet architecture dissected and reconstructed in PyTorch with Imagenette experiments

CNN architecture comparison (ResNet, AlexNet, VGG) for dog breed image classification, benchmarking accuracy against runtime

AlexNet reproduced from the 2012 paper in PyTorch. No torchvision, 60M params verified, 81.0% top-1 on Imagenette in 24 minutes on a laptop GPU.

Deep Learning from scratch: mathematical derivations, manual forward/backward implementations of MLPs, CNNs, RNNs, LSTMs and GRUs, followed by practical PyTorch implementations of modern neural network architectures. Written in Python & PyTorch.

PyTorch project for Van Gogh classification, neural style transfer, Optuna tuning and Grad-CAM model interpretability.

Pre-trained CNN pipeline (VGG-16, ResNet-18, AlexNet) in PyTorch to classify pet images, identify dog breeds, and benchmark accuracy vs. computational efficiency.

CNN-based chest X-ray classifier using AlexNet transfer learning in MATLAB — classified 1,000 images across 4 diagnostic categories, improving accuracy from 84.33% to 90.67% through iterative training across 8/10/12 epochs, with attention to ethical and bias risks in sensitive healthcare imaging.

AI/ML image classification project using pretrained CNN architectures (VGG, ResNet, AlexNet) to classify dogs and dog breeds with Python and performance analysis.

Hands-on TensorFlow & Keras implementations of foundational CNN architectures

Multi-class animal image classification using transfer learning with VGG16, ResNet50, GoogLeNet, and AlexNet.

🐶 Benchmarks VGG16, ResNet18 & AlexNet pretrained CNNs on pet image classification to detect dog breeds and compare model accuracy. Built with Python & PyTorch. | Udacity AIPND Project.

Flask API and PyTorch model behind Time Flies — estimates human subjective duration from video by accumulating salient changes across the layers of an AlexNet classification network and mapping them to time estimates via a pretrained regression stage. Final-year BCS project, University of Sussex.

I implement AlexNet in Pytorch using the CIFAR10 dataset.

A Python desktop GUI (Tkinter) and ESP32 project using a CNN (AlexNet) model to simulate blood group detection from fingerprints. Includes a disclaimer that this is a simulated dummy project.