Pinned Repositories
3D-Detection-Pipeline
A 3D Object detection pipeline using 3D LiDAR points
bevfusion
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
bilibili_project
和bilibili教学视频相关的一些源代码
bpmn-process-analyzer-springboot
Read bpmn diagram and generate all possible processes.
circlehough
Performs Hough transform for circle
cmake-examples
Useful CMake Examples
ienc_handler
An implementation demo to access IENC data in Flanders
Lanelet2
Map handling framework for automated driving
pysbf
Library to parse Septentrio Binary Format (SBF) files in python
sbf_decoder
septentrio binary format decoder
JTShuai's Repositories
JTShuai/ienc_handler
An implementation demo to access IENC data in Flanders
JTShuai/pysbf
Library to parse Septentrio Binary Format (SBF) files in python
JTShuai/sbf_decoder
septentrio binary format decoder
JTShuai/3D-Detection-Pipeline
A 3D Object detection pipeline using 3D LiDAR points
JTShuai/bevfusion
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
JTShuai/bilibili_project
和bilibili教学视频相关的一些源代码
JTShuai/bpmn-process-analyzer-springboot
Read bpmn diagram and generate all possible processes.
JTShuai/circlehough
Performs Hough transform for circle
JTShuai/cmake-examples
Useful CMake Examples
JTShuai/Lanelet2
Map handling framework for automated driving
JTShuai/CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++
JTShuai/GCNv2_SLAM
Real-time SLAM system with deep features
JTShuai/kafka-rpc
RPC protocol based on kafka. Horizontally scalable, fault-tolerant, wicked fast, just like kafka.
JTShuai/kiss-icp
A LiDAR odometry pipeline that just works
JTShuai/LeetCode_Notes
The notes corresponding to LeetCode
JTShuai/lsbaws
Let's Build A Web Server
JTShuai/PointPillars
A Simple PointPillars PyTorch Implementation for 3D LiDAR(KITTI) Detection.
JTShuai/pykafka_rpc
使用Pykafka的正确姿势
JTShuai/rs_driver
RoboSense LiDAR cross-platform driver kernel for advanced development
JTShuai/slambook
JTShuai/tensorflow_cookbook
Code for Tensorflow Machine Learning Cookbook
JTShuai/TIME_Task
Sample task of TIME
JTShuai/Twitter-Emotion-Recognition
With the use of Recurrent Neural Networks, a model is created and trained to learn to recognize emotions in tweets. The dataset has thousands of tweets each classified in one of 6 emotions – love, fear, joy, sadness, surprise and anger. Using TensorFlow as the machine learning framework, this multi class classification problem of the natural language processing domain is solved.
JTShuai/velodyne_decoder
C++/Python Velodyne packet decoder with minimal dependencies