cnn-models

This repo contains implementation of deep learning-based steel surface defect segmentation models. Extensive experiments on several deep learning frameworks have been presented with various performance analysis and comparison.

This research enhances early disease diagnosis by analyzing retinal blood vessels in fundus images using deep learning. It employs eight pre-trained CNN models and Explainable AI techniques.

An end-to-end CNN Image Classification Model which identifies the bird in your image

Food image recognition using deep learning in climate change issue

diffusion model from scratch in python

Learned wavelet-like transform with a hybrid lifting structure for lossy image compression in JPEG2000

End-to-end deep learning pipeline to classify images of dogs and humans to determine what breed the human or dog most resembles

A collection of CNN models are trained on Cloud TPU by using PyTorch/XLA

Solutions to the Advanced CNN course by the Lazy Programmer and all CNN Models I've worked on

Appolo's Ear is an ensemble of three music genre classification neural networks, a nginx server, and a demonstrative react frontend. Its backend is glued together with Docker and Docker compose.

Smart Tagging & Vibe Classification Engine for Fashion Videos 🧥💅🏻👔

Bachelor’s thesis project: A chatbot application for emotion detection in text, integrating Convolutional Neural Network (CNN) models. Developed entirely in Python with Streamlit to provide an interactive and user-friendly interface.

CNN - object detection, classification & various model tuning for prediction optimization

This is an image classification project which was carried out during "Applied Machine Learning and Data Science" in Indian Institute of Technology, Kanpur

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

Implementations of popular Convolutional Neural Networks (CNNs) for image classification and learning. Includes AlexNet, VGG, ResNet, Inception-v1/v3 and more — ideal for study and experimentation.

Colección de Jupyter notes sobre prácticas de algoritmos de Redes Neuronales Artificiales (aprendizaje automático profundo) para generalización, clasificación, detección y análisis exploratorio de datos

A wrapper library over several open source cnn models for tensorflow -2.x.

A collection of deep learning models for rice classification using PyTorch, torchvision, and scikit-learn, with performance metrics evaluated using Slurm jobs.

⚽️A deep learning-based system designed for re-identifying football players across video frames and camera angles using person re-identification techniques. This project combines computer vision, feature extraction, and player tracking to help automate sports analytics and player recognition.