Darknet is a high-performance C-based inference engine and computer vision library designed for real-time object identification and localization. It serves as a neural network framework for training and deploying detection models using the YOLO architecture, providing a toolset for deep learning training and deployment. The project differentiates itself through a C and CUDA implementation that enables hardware acceleration for matrix multiplication and inference speed optimization. It provides a shared library interface for embedding detection capabilities into external applications and suppo
March 15, 2019: for our most updated work on model compression and acceleration, please reference:
ShuffleNet Series by Megvii Research.
megvii-model/shufflenet-series की मुख्य विशेषताएं हैं: Efficient Neural Networks।
megvii-model/shufflenet-series के ओपन-सोर्स विकल्पों में शामिल हैं: alexeyab/darknet — Darknet is a high-performance C-based inference engine and computer vision library designed for real-time object… allenai/xnor-net. forresti/squeezenet. songhan/deep-compression-alexnet — March 15, 2019: for our most updated work on model compression and acceleration, please reference:. tensorflow/models — This repository serves as a centralized collection of state-of-the-art deep learning architectures and reference… wongkinyiu/crossstagepartialnetworks — Cross Stage Partial Networks.