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wangbiao108's Projects

computelibrary icon computelibrary

The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.

cuda-samples icon cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cuda_gemm icon cuda_gemm

A simple high performance CUDA GEMM implementation.

cudnn-samples icon cudnn-samples

This repository contains the CuDNN samples (v7 and v8) developed by NVIDIA for testing the installation

cutlass icon cutlass

CUDA Templates for Linear Algebra Subroutines

cv-cuda icon cv-cuda

CV-CUDA™ is an open-source, GPU accelerated library for cloud-scale image processing and computer vision.

darknet icon darknet

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

datasets icon datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

deep-learning icon deep-learning

Store some of your own in-depth learning code, which is currently in the update stage.The content covers: each algorithm should be implemented in two ways as far as possible (database debugging and self building).

deepdanbooru icon deepdanbooru

AI based multi-label girl image classification system, implemented by using TensorFlow.

deeplearning_objectdetection icon deeplearning_objectdetection

[Deep Learning] Object Detection (深度学习:目标检测与识别—复杂环境下的Logo识别. RCNN系列、TensorFlow)

deeplearningexamples icon deeplearningexamples

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

deepspeed icon deepspeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

deformable-detr icon deformable-detr

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

densenet icon densenet

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

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