Faster_RCNN_for_DOTA
Object detection model
This repository provides code for training a Faster R-CNN object detection model on DOTA datasets.
Code used for training Faster R-CNN on DOTA
336 stars
13 watching
102 forks
Language: Python
last commit: over 6 years ago aerialdetectiondotafaster-rcnn
Related projects:
| Repository | Description | Stars |
|---|---|---|
 ruotianluo/pytorch-faster-rcnn | An implementation of Faster R-CNN detection framework in PyTorch | 1,816 |
| ruotianluo/faster-rcnn-densecap-torch | An implementation of Faster R-CNN object detection in PyTorch, modified from DenseCap. | 85 |
 charlesshang/tffrcnn | A TensorFlow-based implementation of Faster R-CNN object detection using pre-trained ResNet networks and custom datasets. | 874 |
 mitmul/chainer-faster-rcnn | Implementation of object detection using Faster R-CNN with Chainer deep learning framework | 288 |
 longcw/faster_rcnn_pytorch | An implementation of Faster R-CNN using PyTorch | 1,724 |
 eniac-xie/faster-rcnn-resnet | An implementation of Faster R-CNN using ResNet architecture with online hard example mining for object detection | 207 |
 ijkguo/mx-rcnn | An implementation of Faster R-CNN using MXNet for object detection tasks | 671 |
 owlbarn/owl_mask_rcnn | A Mask R-CNN implementation using OCaml's Owl numerical library | 17 |
 xiaolonw/adversarial-frcnn | A Caffe-based implementation of A-Fast-RCNN, a method for object detection using adversarial networks. | 482 |
 wannabeog/mask-rcnn | A PyTorch implementation of the Mask R-CNN architecture | 993 |
 sanghoon/pva-faster-rcnn | Demonstrates a real-time object detection system based on PVANet | 650 |
 mahyarnajibi/fast-rcnn-torch | A Torch implementation of the Fast R-CNN object detection algorithm | 134 |
 andreaskoepf/faster-rcnn.torch | An experimental implementation of a real-time object detection system using a neural network with region proposal generation. | 122 |
 shaoqingren/faster_rcnn | An object detection framework using deep convolutional networks and region proposal networks. | 2,712 |
 randl/shufflenetv2-pytorch | An implementation of a lightweight convolutional neural network architecture for mobile devices | 191 |