A paper list of object detection using deep learning.
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Updated
Feb 12, 2024 - Python
A paper list of object detection using deep learning.
This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! NoCode training with TensorFlow has never been so easy.
State-of-the-art Single Shot MultiBox Detector in Pure TensorFlow, QQ Group: 758790869
This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. N…
Includes: Learning data augmentation strategies for object detection | GridMask data augmentation | Augmentation for small object detection in Numpy. Use RetinaNet with ResNet-18 to test these methods on VOC and KITTI.
Light-Head RCNN and One Novel Object Detector
Automatic Annotation tool for labelling images in bulk with their corresponding bounding box annotations.
Pytorch implementation of the 'Slim-neck by GSConv: a lightweight-design for real-time detector architectures'
Keras implementation of RetinaNet for object detection and visual relationship identification
TensorFlow and Pytorch practice codes with purity and simplicity.
Eye detection in python with opencv
YOLO Algorithm (Yolov2 model) trained on COCO Dataset for Object Detection
MobileNetV2 architecture combined with a dynamically generated Feature Pyramid Network
Historical OpenStreetMap Objects to Machine Learning Training Samples
OpenCV Webservices in a Docker container.
This repository contains the code for real-time object detection. I'm using video stream coming from webcam. MobileNet-SSD and OpenCv has been used as base-line approach. TensorFlow object detection API has been used in revised approach.
Real-time object detection and tracking for autonomous driving.
This is the github project for the F1Tenth Independent Study Projects 2021. In this project we are focusing on the development of different approaches to achieve object detection and tracking based on 2D LiDAR.
Detection of vehicles using Image processing.
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