Mobile Deep Learning
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Open3d | 10,396 | 15 days ago | 1,018 | other | C++ | |||||
| Open3D: A Modern Library for 3D Data Processing | ||||||||||
| Raspberrypi | 2,165 | 5 years ago | 24 | Assembly | ||||||
| Raspberry Pi ARM based bare metal examples | ||||||||||
| Userland | 2,016 | 6 months ago | 103 | bsd-3-clause | C | |||||
| Source code for ARM side libraries for interfacing to Raspberry Pi GPU. | ||||||||||
| Bmf | 595 | 3 months ago | 4 | August 22, 2023 | 19 | apache-2.0 | C++ | |||
| Cross-platform, customizable multimedia/video processing framework. With strong GPU acceleration, heterogeneous design, multi-language support, easy to use, multi-framework compatible and high performance, the framework is ideal for transcoding, AI inference, algorithm integration, live video streaming, and more. | ||||||||||
| Anakin | 492 | 4 years ago | 68 | apache-2.0 | C++ | |||||
| High performance Cross-platform Inference-engine, you could run Anakin on x86-cpu,arm, nv-gpu, amd-gpu,bitmain and cambricon devices. | ||||||||||
| In Prestissimo | 267 | 6 years ago | 2 | other | C++ | |||||
| A very fast neural network computing framework optimized for mobile platforms.QQ group: 676883532 【验证信息输：绝影】 | ||||||||||
| Tvm Mali | 145 | 6 years ago | 2 | mit | C | |||||
| Optimizing Mobile Deep Learning on ARM GPU with TVM | ||||||||||
| Cnn Inference Engine Quick View | 142 | 2 years ago | ||||||||
| A quick view of high-performance convolution neural networks (CNNs) inference engines on mobile devices. | ||||||||||
| Ncnn Android Squeezenet | 133 | 6 months ago | 11 | C++ | ||||||
| The squeezenet image classification android example | ||||||||||
| Fdtd3d | 98 | 7 months ago | gpl-2.0 | C++ | ||||||
| fdtd3d is an open source 1D, 2D, 3D FDTD electromagnetics solver with MPI, OpenMP and CUDA support for x64, ARM, ARM64, RISC-V, PowerPC architectures | ||||||||||
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