University1652 Baseline
ACM Multimedia2020 University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization 🚁 annotates 1652 buildings in 72 universities around the world.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Gpytorch | 3,337 |  | 4 | 79 | 3 months ago | 38 | June 02, 2023 | 343 | mit | Python |
| A highly efficient implementation of Gaussian Processes in PyTorch | ||||||||||
| Cs231n 2017 | 524 | a year ago | 4 | Jupyter Notebook | ||||||
| Completed the CS231n 2017 spring assignments from Stanford university | ||||||||||
| University1652 Baseline | 402 | 3 months ago | 15 | mit | Python | |||||
| ACM Multimedia2020 University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization :helicopter: annotates 1652 buildings in 72 universities around the world. | ||||||||||
| Kenlg Reading | 393 | 2 years ago | ||||||||
| Author: Wenhao Yu ([email protected]). ACM Computing Survey'22. Reading list for knowledge-enhanced text generation, with a survey. | ||||||||||
| Real Time Network | 374 | 2 years ago | 1 | |||||||
| real-time network architecture for mobile devices and semantic segmentation | ||||||||||
| Mongolian Nlp | 126 | a year ago | Jupyter Notebook | |||||||
| Useful resources for Mongolian NLP | ||||||||||
| Real Time Object Detection For Autonomous Driving Using Deep Learning | 17 | 3 years ago | mit | Jupyter Notebook | ||||||
| My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset. | ||||||||||
| Towards Explainable Ai System For Traffic Sign Recognition And Deployment In A Simulated Environment | 15 | 3 years ago | mit | C# | ||||||
| This project is part of the CS course 'Systems Engineering Meets Life Sciences I' at Goethe University Frankfurt. In this Computer Vision project, we present our first attempt at tackling the problem of traffic sign recognition using a systems engineering approach. | ||||||||||
| Hyperspectral Images Classification In Pytorch With Multiple Gpus | 9 | 4 years ago | mit | Python | ||||||
| Hyperspectral Images Classification in Pytorch with multiple GPUs - Pavia University | ||||||||||
| Subway Station Hazard Detection | 5 | 3 years ago | n,ull | mit | Jupyter Notebook | |||||
| This project is part of the CS course 'Systems Engineering Meets Life Sciences II' at Goethe University Frankfurt. In this Computer Vision project, we developed a first prototype of a security system which uses the surveillance cameras at subway stations to recognize dangerous situations. The training data was artificially generated by a Unity-based simulation. | ||||||||||
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