Pinned Repositories
UOS_festival
2018년 서울시립대학교 축제에서 제공될 컨텐츠 페이지 입니다.
armnn
Arm NN ML software
Caffe-HRT
Heterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original Caffe architecture which users deploy their applications seamlessly.
caffe-model-zoo
caffe pretrained models and prototxt
caffe-train
caffe-tucker-resnet
Caffe implementation of tucker tensor decomposition for convolutional layers
mcunet
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
once-for-all
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
tflite-micro
Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).
tinyengine
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory
gunjupark's Repositories
gunjupark/armnn
Arm NN ML software
gunjupark/Caffe-HRT
Heterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original Caffe architecture which users deploy their applications seamlessly.
gunjupark/caffe-model-zoo
caffe pretrained models and prototxt
gunjupark/caffe-tucker-resnet
Caffe implementation of tucker tensor decomposition for convolutional layers
gunjupark/coding
coding test practice
gunjupark/mcunet
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
gunjupark/once-for-all
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
gunjupark/tflite-micro
Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).
gunjupark/tinyengine
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory
gunjupark/CUDALibrarySamples
CUDA Library Samples
gunjupark/DS-Net
DSNet cuda11 포팅 관련
gunjupark/gunjupark.github.io
Like lion's html, css source file
gunjupark/jetson_stats
📊 Simple package for monitoring and control your NVIDIA Jetson [Xavier NX, Nano, AGX Xavier, TX1, TX2]
gunjupark/MobileNet-v2-caffe
MobileNet-v2 experimental network description for caffe
gunjupark/OndeviceDLPaperReview
Ondevice Deep Learning Papers Review & summary
gunjupark/OpenCL-Headers
Khronos OpenCL-Headers
gunjupark/paper_reproduce_study
Pytorch 및 TF2.0 논문 구현 스터디 입니다.
gunjupark/ResNet-18-Caffemodel-on-ImageNet
ResNet-18 Caffemodel @ilsvrc12 shrt 256 with Top-1 69% Top-5 89%
gunjupark/SqueezeNet
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters
gunjupark/SW_engeneering
gunjupark/Tengine
Tengine is a lite, high performance, modular inference engine for embedded device
gunjupark/tensorflow
An Open Source Machine Learning Framework for Everyone
gunjupark/tensorflow-yolov4-tflite
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
gunjupark/test
gunjupark/test_1
gunjupark/test_repo
04/11 git class
gunjupark/testproject
gunjupark/utopia
해커톤 유토피아
gunjupark/utopia2018
2018 해커톤 개발
gunjupark/visual-slam-roadmap
Roadmap to becoming a Visual-SLAM developer in 2021