Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection (Tensor Cores are used)
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Updated
Apr 30, 2019 - C
Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection (Tensor Cores are used)
deep learning convolutional neural network implemented with SIMD acceleration (auto-vectorization)
PROJECT: VGG16 Acceleration using OpenCL
CPU Optimized & IoT Capable Embedded Computer Vision & Machine Learning Library.
Deep neural network. Uses CUDA with cuDNN and cuBLAS_v2 libraries. Provides flexible model building. As an example, classificates cell Images for detecting malaria.
A Cross Platform Convolution Neural Network Library
Modifying pretrained yolo v3
Rede convolucional em C. Camadas Conv, ConvNc, Pool, PoolAv, Relu, Softmax, BatchNorm, DropOut, FullConnect.
A machine learning trigger bot for Quake3 Arena & Quake Live.
Speckle2Speckle based despeckling filter for TerraSAR-X Spotlight mode, trained on Colima
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