It has never been rare among AI researchers that combine and evaluate different models to discover their methods. When I read about Retinanet and Efficientnet, I had a mind to combine them.

Pneumonia Detection using Convolutional Neural Networks (RetinaNet)

This project is a part of my Multidisciplinary Project in semester 242 which aims to develop AI models for detecting diseases in bok choy plants. The project leverages deep learning techniques and distributed training to ensure scalability and efficiency.

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

A Pytorch implementation of the Retinanet, based on the implementation by @yhenon

Keras RetinaNet 工程实践

Official implementation of the papr 'A Study on Traffic Vulnerable Detection Using Object Detection-Based Esemble'

Итоговый проект. Реализация модели детекции и ее встраивание в реальное приложение на python

Pre-trained coco model for detection with retinanet using camera to object detection.

PyTorch implementation of Anchor-Maker and Anchor-Assigner

A simple and deeply commented PyTorch implementation of the RetinaNet paper, built as an educational resource. 📚 Demystify the core concepts of object detection with code that sticks closely to the original paper. 💡

Retina U-Net for medical imaging detection toolkit

Detection of persons in a video

This project for implementing RetinaNet with TF/Keras 1.14, I converted it from Keras Code example (TF2X) and tried to use tfrecord for fast training.

Object Detection codes written in Tensorflow and PyTorch.

Developed a deep learning predictive model that can determine, given an intersection image, the class and location of the objects objects of two types (car or truck).

RetinaNet-based AML and immune cell detection from multi-channel microscopy images.

Re-implement RetinaNet for object detection tasks