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clustering-with-deep-learning

Generic implementation for clustering with deep learning : representation learning (DNN) + clustering

cmsis_5

CMSIS Version 5 Development Repository

cnn-for-face-image-retrieval

:apple:Face image rerieval

cnnimageretrieval

CNNImageRetrieval: Training and evaluating CNNs for Image Retrieval

cnnimageretrieval-pytorch

CNN Image Retrieval in PyTorch: Training and evaluating CNNs for Image Retrieval in PyTorch

cnn_graph

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

cnn_head_detection

Code for ICCV 2015 paper "Context-aware CNNs for person head detection"

compiler-explorer

Run compilers interactively from your web browser and interact with the assembly

continuous-convop

The Continuous Convolution Operator Tracker (C-COT).

convert_caltech_annos_to_yolo

This script will convert caltech annotations into yolo format

convert_mot16_to_yolo

Converts MOT16 annotations to YOLO format.

convex.jl

A Julia package for disciplined convex programming

convolutional-pose-machines-tensorflow

cornernet

coursera-archive

Coursera Archive

cs-notes

:books: Tech Interview Guide 技术面试必备基础知识、Leetcode 题解、Java、C++、Python、后端面试、操作系统、计算机网络、系统设计

cs229t

Statistical Learning Theory (CS229T) Lecture Notes

cs294-ai-sys-sp19

CS294; AI For Systems and Systems For AI

csrcolor

Efficient and High-quality Graph Coloring on the GPU

ctf-writeups

Collection of scripts and writeups

ctrnet-tool

This's the tool for CTR, including FM, FFM, NFFM and so on.

cuda-connected-component-labelling

Parallel GPU Implementation of Connected Component Labelling (CCL). Connected-component labeling is used in computer vision to detect connected regions in binary digital images

cudf

cuDF - GPU DataFrame Library

cuml

cuML - RAPIDS Machine Learning Library

cvat

Powerful and efficient Computer Vision Annotion Tool (CVAT)

d2-net

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

dac

dac-hdc-2018-object-detection-in-jetson-tx2

dac2018

code submitted to DAC2018(http://www.cse.cuhk.edu.hk/~byu/2018-DAC-HDC/index.html)

dac2018-tgiif

The 1st place winner's source codes for DAC 2018 System Design Contest, FPGA Track