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embedded-ai.bi-weekly

WeChat: NeuralTalk，Weekly report and awesome list of embedded-ai.
https://github.com/ysh329/embedded-ai.bi-weekly

Last synced: 3 days ago
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GPU Device
- Adreno – Wikipedia
- GPU GFLOPS | surge.sh
- 手机处理器天梯图_最新CPU天梯图_手机CPU性能天梯图 | ZOL中关村在线
FrameworkPaper
- MobiSys '16
- MobiCASE '16
- MM '16
- 1605.04614
- MobiSys '17
- MobiSys '17
- EMDL '17
- IPSN '16
- ISCA '16
- 怎么把人脸检测的速度做到极致
- 基于OpenGL ES 的深度学习框架编写 - jxt1234and2010的专栏 - CSDN博客
- 怎么把人脸检测的速度做到极致
- 怎么把人脸检测的速度做到极致
Uncategorized
- Uncategorized
  - 高通处理器规格表 | mydriver
CPU Devive
- 高通骁龙处理器排行榜,强大性能一览无余 | Qualcomm
- 手机CPU性能天梯图 CPU performance of mobile comparison | mydriver
Classic
- 1512.03385
- 1610.02357
- 1611.05431
Overview
- 1703.09039
- 1707.01209
- 1707.04319
Representation
- 1707.09926
- 1608.01409
- IoT-App ’15
- SenSys ’16
Structure
- 1704.06904 - attention-network)
- BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks
- CVPR2017
- 1707.06342
- 1707.01083
- 1704.04861
- 1707.06990
- 1706.03912
- 1704.06904 - attention-network)
Binarization
- CVPR2017
- 1707.04693
- 1602.02830
- 1603.05279
- 1705.09864
- 1606.06160
Pruning
- CVPR'17
- ICLR'17
- ICLR'17
- ICLR'17
- ICLR'16
- NIPS'16
- NIPS'15
Quantization
- ICML'17
- 1412.6115
- CVPR '16
- ICASSP'16
- arXiv'16
- ICLR'17
- ICLR'17
- CVPR'17
- 1706.02393
LowRankApproximation
- CVPR'15
- Accelerating Very Deep Convolutional Networks for Classification and Detection
- 1511.06067
- NIPS'14
- ICLR'16
Distillation
- 1503.02531
- Face Model Compression by Distilling Knowledge from Neurons
Joint Compression
- 1707.09102
Kernel Selection
- 1703.09746
Computation Precison/Resolution
- ICML2017
- 1707.09068
- 1708.00999
Model Split
- ASPLOS’17
- 1705.04630
Others
- 1608.02893
- 1608.05148
- 1707.09422
- 1707.09855
- 1707.09597
- 1604.08772
- 1606.05316
Android
- TensorFlow Android Camera Demo
iOS
- Compile MXnet on Xcode (in Chinese) - a step-by-step tutorial of compiling MXnet on Xcode for iOS app
- KimDarren/FaceCropper: Crop faces, inside of your image, with iOS 11 Vision api.
Frameworks & Acceleration Library
- Apple CoreML
- Deep Learning in a Single File for Smart Devices — mxnet
Other Toolkit
- Samsung/iotjs: Platform for Internet of Things with JavaScript
- HandNet - A dataset of depth images of hands
- Deep learning **systems**: UW course schedule(focused on systems design, not learning)
- Squeezing Deep Learning Into Mobile Phones
- Efficient Convolutional Neural Network Inference on Mobile GPUs
- pdf
- Optimal Compute on ARM MaliTM GPUs
- Compute for Mobile Devices Performance focused
- Hands On OpenCL
- Better OpenCL Performance on Qualcomm Adreno GPU
- Tutorial on Hardware Architectures for Deep Neural Networks | MIT MICRO-50
- 基于mtcnn和facenet的实时人脸检测与识别系统开发 | 知乎专栏
- Creating insanely fast image classifiers with MobileNet in TensorFlow | HACKERNOON
- How to squeeze the most from your training data | KDNUGGETS
- Ubuntu16.04腾讯NCNN框架入门到应用 | CSDN
- Building Cross-Platform CUDA Applications with CMake | NVIDIA
- Caffe2 Bay Area Meetup (5/31/2017) | YouTube
- How to squeeze the most from your training data | KDNUGGETS
- Deep Learning – Tutorial and Recent Trends
Hardware
- GPU
Mobile Video Process Library/Player
- Pili-完美直播体验（Pili Streaming Cloud）

Programming Languages

Categories

Hardware 36 Other Toolkit 19 FrameworkPaper 13 Quantization 9 Structure 9 Others 7 Pruning 7 Binarization 6 LowRankApproximation 5 Representation 4 Computation Precison/Resolution 3 GPU Device 3 Overview 3 Classic 3 Distillation 2 Model Split 2 Frameworks & Acceleration Library 2 iOS 2 CPU Devive 2 Joint Compression 1 Uncategorized 1 Kernel Selection 1 Mobile Video Process Library/Player 1 Android 1

Sub Categories

GPU 36 Uncategorized 1

Keywords

vision-api 1 vision 1 swift 1 ios11 1 ios 1 face-recognition 1 face-detection 1 face 1