Shounak Chakraborty (ShounakCy)

ShounakCy

Geek Repo

Company:@Northvolt | @Smarc-project

Location:Stockholm, Sweden

Home Page:https://www.linkedin.com/in/shounak-chakraborty13/

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Shounak Chakraborty's repositories

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ros-robotics-companies

A list of robotics companies using the Robot Operating System (ROS and ROS 2).

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LeetCode

💡 LeetCode in C++/Java/Python (respect coding conventions)

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PiP-Planning-informed-Prediction

(ECCV 2020) PiP: Planning-informed Trajectory Prediction for Autonomous Driving

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awesome-visual-slam

:books: The list of vision-based SLAM / Visual Odometry open source, blogs, and papers

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stdan

the code of stdan

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havsim

A differentiable traffic simulator for calibration of traffic models and optimization of AV behavior

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Lane-changing-duration-analysis

Comprehensive survival analysis of lane-changing duration

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irlmodelvalidation

This python package contains scripts needed to train IRL Driver models on HighD datasets. This code is accompanying the paper "Validating human driver models for interaction-aware automated vehicle controllers: A human factors approach - Siebinga, Zgonnikov & Abbink 2021" and should be used in combination with TraViA, a program for traffic data visualization and annotation.

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SimulationFrameworkPublic

A stable and public version of SimulationFramework for KIT Robot Praktikum usage

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CLOCs

CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection

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smarc_missions

🟢 Behavior trees and such for different missions

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smarc_perception

Perception algorithms for underwater sonars and cameras

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smarc_navigation

🟢 Visual odometry, localization, slam for the SMARC auvs

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build-your-own-x

🤓 Build your own (insert technology here)

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DeepLearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06

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imc_ros_bridge

🟢 Minimal library for bridging ROS and IMC messages

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PyTrafficSim

PyTrafficSim is a light traffic simulator for research related purposes. PTS is the most easy way to test your self-driving algorithm within a complicated intersection scenario.

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Recommendation-System-using-similarity

Recommendation System using similarity of products

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Forecasting

Statistical, ML, DL

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PID-Controlled-Robots

Designed PID controlled Line Follower and Maze Follower Robots

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