Abhinav Gupta (abhinavG37)

abhinavG37

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Company:Northeastern University

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Abhinav Gupta's repositories

mobile_robotics

Codes for the EECE_5552 Assisgnments (Fall 2021, Northeastern University)

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awesome-lane-detection

A paper list of lane detection.

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bebop-eece5550

Working repository for Team Bebop in EECE-5550 Mobile Robotics at Northeastern University.

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EECE5554_RoboticSensingAndNavigation

Code repo for assignments in the Spring 22 edition of Robotics Sensing and Navigation at Northeastern University

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Complex-YOLOv4-Pytorch

The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"

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DL4CVStarterBundle

Edited code examples from the book 'Deep Learning for Computer Vision - Starter Bundle' by Adrian Rosebrock

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ED_Lib

Implementations of edge (ED, EDColor, EDPF), line (EDLines), circle and low eccentric ellipse (EDCircles) detection algorithms.

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github-readme-stats

:zap: Dynamically generated stats for your github readmes

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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.

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kitti-pcl

Code to use the KITTI (http://www.cvlibs.net/datasets/kitti) data set with PCL

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KITTI_Tutorial

Tutorial for using Kitti dataset easily

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lane_detection_advanced_sliding_windows

Lane detection for ADAS application with sliding windows technics

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open-source-rover

A build-it-yourself, 6-wheel rover based on the rovers on Mars!

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opencv

Open Source Computer Vision Library

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PythonRobotics

Python sample codes for robotics algorithms.

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rfid_locatron

Assistive Robotics project to locate missing objects in a predefined space.

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sklearn_tutorial

Materials for my scikit-learn tutorial

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tintindas

Custom profile for tintindas

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Udacity-Advance-Lane-detection-of-the-road

Udacity Self-Driving Car Engineer Nanodegree Advanced Lane Finding Project. Identifying lanes using edge detection (Sobel operator, gradient of magnitude and direction, and HLS color space), camera calibration and unwarping (distortion correction and perspective transform), and polynomial fitting for the lanes.

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