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20202025
most citedMulti-Modal Fusion for Sensorimotor Coordination in Steering Angle Prediction

1 citations · 2 across the 7 of their papers we have counts for

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cs.CV2023

Radar-Lidar Fusion for Object Detection by Designing Effective Convolution Networks

Farzeen Munir, Shoaib Azam, Tomasz Kucner +2

Object detection is a core component of perception systems, providing the ego vehicle with information about its surroundings to ensure safe route planning. While cameras and Lidar…

cs.CV2022★ 1 cited

Multi-Modal Fusion for Sensorimotor Coordination in Steering Angle Prediction

Farzeen Munir, Shoaib Azam, Byung-Geun Lee +1

Imitation learning is employed to learn sensorimotor coordination for steering angle prediction in an end-to-end fashion requires expert demonstrations. These expert demonstrations…

cs.CV2021

ARTSeg: Employing Attention for Thermal images Semantic Segmentation

Farzeen Munir, Shoaib Azam, Unse Fatima +1

The research advancements have made the neural network algorithms deployed in the autonomous vehicle to perceive the surrounding. The standard exteroceptive sensors that are utiliz…

cs.CV2021

SSTN: Self-Supervised Domain Adaptation Thermal Object Detection for Autonomous Driving

Farzeen Munir, Shoaib Azam, Moongu Jeon

The sensibility and sensitivity of the environment play a decisive role in the safe and secure operation of autonomous vehicles. This perception of the surrounding is way similar t…

cs.CV2021

Channel Boosting Feature Ensemble for Radar-based Object Detection

Shoaib Azam, Farzeen Munir, Moongu Jeon

Autonomous vehicles are conceived to provide safe and secure services by validating the safety standards as indicated by SOTIF-ISO/PAS-21448 (Safety of the intended functionality).…

cs.CV2020

LDNet: End-to-End Lane Marking Detection Approach Using a Dynamic Vision Sensor

Farzeen Munir, Shoaib Azam, Moongu Jeon +2

Modern vehicles are equipped with various driver-assistance systems, including automatic lane keeping, which prevents unintended lane departures. Traditional lane detection methods…