OpenMMLab Detection Toolbox and Benchmark
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Updated
May 24, 2024 - Python
OpenMMLab Detection Toolbox and Benchmark
Blood Cells Detection with RetinaNet - ResNet-50 from the TensorFlow Model Garden
Officiel implementation of the paper " FlightScope: A Deep Comprehensive Assessment of Aircraft Detection Algorithms in Satellite Imagery "
This research delves into the applications CNNs in crowd detection, a domain critical for optimizing operations, ensuring safety, and making informed decisions in diverse industries.
convert mmdetection model to tensorrt, support fp16, int8, batch input, dynamic shape etc.
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.
[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021
An (unofficial) implementation of Focal Loss, as described in the RetinaNet paper, generalized to the multi-class case.
This project is completed as a fulfilment for the CDS590 Consultancy Project & Practicum provided by School of Computer Sciences, USM as part of their Masters of Science in Data Science and Analytics program.
benchmark of object detection algorithms for license plate detection
Implementation of CVPR 2020 paper "EfficientDet: Scalable and Efficient Object Detection" using PyTorch and OpenCV
AAI-521: Intro to Computer Vision - Final Project - 12/11/2023
Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'
Repository of the project for the course of Symbolic and Evolutionary Artificial Intelligence, AIDE unipi
Evaluation of different object detection models for real-time detection on the COCO 2017 dataset. Implementation of a real-time detection model of medical masks on human faces based on YOLOv5 using the PWMFD dataset.
YOLO Series
A restaurant food ordering system leveraging RetinaNet for sign language detection and LLM for seamless order processing.
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