Pinned Repositories
AIPND
Udacity 担任助教时候的AIPND知识点总结
bev_lane_det
book-1
CUDA-Programming-Guide-in-Chinese
This is a Chinese translation of the CUDA programming guide
darknet-trt
DCAMA
This is the official implementation of the ECCV'2022 paper "Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation".
deep-learning-from-scratch-3
『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)
nvidia-digits-install-docker
pjreddie-vision
https://pjreddie.com/courses/computer-vision
statistical-learning-method
Machine Leaning
ANGDL's Repositories
ANGDL/CUDA-Programming-Guide-in-Chinese
This is a Chinese translation of the CUDA programming guide
ANGDL/nvidia-digits-install-docker
ANGDL/pjreddie-vision
https://pjreddie.com/courses/computer-vision
ANGDL/statistical-learning-method
Machine Leaning
ANGDL/AIPND
Udacity 担任助教时候的AIPND知识点总结
ANGDL/bev_lane_det
ANGDL/book-1
ANGDL/darknet-trt
ANGDL/DCAMA
This is the official implementation of the ECCV'2022 paper "Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation".
ANGDL/deep-learning-from-scratch-3
『ゼロから作る Deep Learning ❸』(O'Reilly Japan, 2020)
ANGDL/detr
End-to-End Object Detection with Transformers
ANGDL/face
ANGDL/gather_elements
Pytorch gather cuda implementation
ANGDL/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
ANGDL/MetaNN
ANGDL/Object-Detection-Metrics
Most popular metrics used to evaluate object detection algorithms.
ANGDL/onnx-tensorrt
ONNX-TensorRT: TensorRT backend for ONNX
ANGDL/opencv_build_3.4.7
opencv_build_3.4.7
ANGDL/PFENet
PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation (TPAMI).
ANGDL/pypcd
PCL pcd fileformat i/o in Python
ANGDL/PyTorch-YOLOv3
Minimal PyTorch implementation of YOLOv3
ANGDL/simple-sudoku
上传数独截图，解题
ANGDL/SparseConvNet-archived
Spatially-sparse convolutional networks. Allows processing of sparse 2, 3 and 4 dimensional data.Build CNNs on the square/cubic/hypercubic or triangular/tetrahedral/hyper-tetrahedral lattices.
ANGDL/vision-hw1