Real-Time Semantic Segmentation Using Hyperspectral Images for Unstructured and Unknown Environments-Reference-Cited by-同舟云学术

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Real-Time Semantic Segmentation Using Hyperspectral Images for Unstructured and Unknown Environments

Published:2023-10-31 Issue: Volume: Page:
ISSN:
Container-title:2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
language:
Short-container-title:

Author:

Medellin Anthony¹,Bhamri Anant¹,Langari Reza¹,Gopalswamy Swaminathan¹

Affiliation:

1. Texas A&M University,Mechanical Engineering Department,College Station,TX,USA

Funder

Arm

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10430415/10430497/10431091.pdf?arnumber=10431091

Reference24 articles.

1. Semantic world model for off-road environments for autonomous navigation and decision making;Bhamri

2. LiDARNet: A Boundary-Aware Domain Adaptation Model for Point Cloud Semantic Segmentation

3. CCNet: Criss-Cross Attention for Semantic Segmentation

4. Review the state-of-the-art technologies of semantic segmentation based on deep learning

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1. Fine-Scale Mangrove Species Classification Based on UAV Multispectral and Hyperspectral Remote Sensing Using Machine Learning;Remote Sensing;2024-08-22

2. Unifying Ontological Framework for All-Terrain Datasets;2023 Seventh IEEE International Conference on Robotic Computing (IRC);2023-12-11

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