Real-time semantic segmentation for autonomous driving: A review of CNNs, Transformers, and Beyond DOI Creative Commons
Mohammed A. M. Elhassan, Changjun Zhou, Ali Khan

и другие.

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2024, Номер 36(10), С. 102226 - 102226

Опубликована: Ноя. 4, 2024

Язык: Английский

AMT-Net: Attention-based multi-task network for scene depth and semantics prediction in assistive navigation DOI Creative Commons
Yunjia Lei, Joshua Thompson, Son Lam Phung

и другие.

Neurocomputing, Год журнала: 2025, Номер unknown, С. 129468 - 129468

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
A Review on Recent Deep Learning-Based Semantic Segmentation for Urban Greenness Measurement DOI Creative Commons
Doo Hong Lee,

Hye Yeon Park,

Joonwhoan Lee

и другие.

Sensors, Год журнала: 2024, Номер 24(7), С. 2245 - 2245

Опубликована: Март 31, 2024

Accurate urban green space (UGS) measurement has become crucial for landscape analysis. This paper reviews the recent technological breakthroughs in deep learning (DL)-based semantic segmentation, emphasizing efficient analysis, and integrating greenness measurements. It explores quantitative measures applied through categorized into plan view- perspective view-based methods, like Land Class Classification (LCC) with objects Green View Index (GVI) based on street photographs. review navigates from traditional to modern DL-based segmentation models, illuminating evolution of tasks advanced also presents typical performance metrics public datasets constructing these measures. The results show that accurate (semantic) is inevitable not only fine-grained but qualitative evaluation analyses planning amidst incomplete explainability DL model. Also, unsupervised domain adaptation (UDA) aerial images addressed overcome scale changes lack labeled data contributes helping researchers understand technology challenging topics UGS research.

Язык: Английский

Процитировано

3
Accelerated semantic segmentation of additively manufactured metal matrix composites: Generating datasets, evaluating convolutional and transformer models, and developing the MicroSegQ+ Tool DOI
Mutahar Safdar,

Yi Fan Li,

Randy El Haddad

и другие.

Expert Systems with Applications, Год журнала: 2024, Номер 251, С. 123974 - 123974

Опубликована: Апрель 13, 2024

Язык: Английский

Процитировано

3
PSO-based lightweight neural architecture search for object detection DOI
Tao Gong, Yongjie Ma

Swarm and Evolutionary Computation, Год журнала: 2024, Номер 90, С. 101684 - 101684

Опубликована: Авг. 2, 2024

Язык: Английский

Процитировано

3
Real-time semantic segmentation for autonomous driving: A review of CNNs, Transformers, and Beyond DOI Creative Commons
Mohammed A. M. Elhassan, Changjun Zhou, Ali Khan

и другие.

Journal of King Saud University - Computer and Information Sciences, Год журнала: 2024, Номер 36(10), С. 102226 - 102226

Опубликована: Ноя. 4, 2024

Язык: Английский

Процитировано

3