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Academic Articles & Research Papers
Showing 20 of 24 academic articles
Huaqi Zhao, Songnan Zhang, Xiang Peng, Zhengguang Lu et al. • Frontiers in Neurorobotics
(2025)
Object detection is a critical component in the development of autonomous driving technology and has demonstrated significant growth potential. To address the limitations of current techniques, this paper presents an improved object detecti...
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Open Access (DOAJ)
DOI: 10.3389/fnbot.2024.1484276
Michele Guagnano, Sara Groppo, Luigi Pugliese, Massimo Violante • Sensors
(2025)
In many applications, recognizing the depth of sleep (e.g., light, deep, REM sleep) while the subject is sleeping enables innovative features. For instance, in SAE Level 4 autonomous driving, a driver may need to takeover the vehicle contro...
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Open Access (DOAJ)
DOI: 10.3390/s25072141
Seungjae Han, Taeyoung Oh, Soohyeon Lee, Siyeong Park et al. • Applied Sciences
(2025)
With continuous advancements in autonomous driving technology, systematic and reliable safety verification is becoming increasingly important. However, despite the active development of various X-in-the-loop simulation (XILS) platforms to v...
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Open Access (DOAJ)
DOI: 10.3390/app15126545
Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu et al. • IEEE Access
(2024)
Autonomous driving technology plays a key role in addressing traffic safety issues and relieving traffic congestion by virtue of its capabilities of enabling accurate environmental perception and real-time response. Aiming at the problem of...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3509694
Sotirios Spanogianopoulos, Kenan Ahiska • European Transport Research Review
(2026)
Abstract Adverse weather conditions, such as snow, heavy rain, fog, or limited illumination, pose significant challenges for autonomous vehicles (AVs) by degrading sensor reliability. This paper introduces E2ETrADS, an end-to-end transforme...
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Open Access (DOAJ)
DOI: 10.1186/s12544-026-00793-6
Yousik Lee, Samuel Woo, Yunkeun Song, Jungho Lee et al. • IEEE Access
(2020)
Emerging trends that are shaping the future of the automotive industry include electrification, autonomous driving, sharing, and connectivity, and these trends keep changing annually. Thus, the automotive industry is shifting from mechanica...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3004661
Suyang Xi, Zihan Liu, Ziming Wang, Qiang Zhang et al. • IEEE Access
(2024)
Lane detection is fundamental to autonomous driving, yet remains challenging in complex environments with occlusions, ambiguous markings, and varied lighting. We introduce the Global Semantic Enhancement Network (GSENet), a groundbreaking f...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3429396
SHA Yuyang, LU Jingtao, DU Haofan, ZHAI Xiaobing, MENG Weiyu, LIAN Xu, LUO Gang, LI Kefeng • Jisuanji gongcheng
(2025)
Image segmentation is a crucial technology for environmental perception, and it is widely used in various scenarios such as autonomous driving and virtual reality. With the rapid development of technology, computer vision-based blind guidin...
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Open Access (DOAJ)
DOI: 10.19678/j.issn.1000-3428.0068674
Congcong Zhang, Jin Tian, Lihua Gong, Yujin Zhang et al. • Applied Sciences
(2026)
Video prediction is a fundamental task in computer vision with broad applications in intelligent robotics, autonomous driving, and related fields. However, existing methods often struggle to simultaneously model long-term temporal dependenc...
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Open Access (DOAJ)
DOI: 10.3390/app16094423
Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access
(2020)
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3039858
Yejin Jung, Sunwoo Cho, Haeyoon Yang, Nam Ik Cho • IEEE Access
(2025)
Semantic segmentation assigns class labels at the pixel level, forming a key part of various computer vision applications, including autonomous driving, medical imaging, and robotics. However, segmentation accuracy often drops significantly...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3641590
Václav Diviš, Bastian Spatz, Marek Hrúz • AI
(2024)
Recent research has drawn attention to the ambiguity surrounding the definition and learnability of Out-of-Distribution recognition. Although the original problem remains unsolved, the term “Out-of-Model Scope” detection offers a clearer pe...
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Open Access (DOAJ)
DOI: 10.3390/ai5040104
Andrei Mihalea, Adina Magda Florea • Applied Sciences
(2024)
Computer vision has significantly influenced recent advancements in autonomous driving by providing cutting-edge solutions for various challenges, including object detection, semantic segmentation, and comprehensive scene understanding. One...
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Open Access (DOAJ)
DOI: 10.3390/app14177776
Daniel A. Hashimoto, Guy Rosman, Elan R. Witkowski, Caitlin E. Stafford et al. • Annals of Surgery
(2019)
OBJECTIVE(S): To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG). BACKGROUND: Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by comput...
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Open Access
DOI: https://doi.org/10.1097/sla.0000000000003460
PMC: 7216040
Simegnew Yihunie Alaba, Ali C. Gurbuz, John E. Ball • World Electric Vehicle Journal
(2024)
The pursuit of autonomous driving relies on developing perception systems capable of making accurate, robust, and rapid decisions to interpret the driving environment effectively. Object detection is crucial for understanding the environmen...
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Open Access (DOAJ)
DOI: 10.3390/wevj15010020
Xuefei Yu, Jinan Gu, Zedong Huang, Zhijie Zhang • PLoS ONE
(2022)
Recent stereo matching methods, especially end-to-end deep stereo matching networks, have achieved remarkable performance in the fields of autonomous driving and depth sensing. However, state-of-the-art stereo algorithms, even with the deep...
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Open Access (DOAJ)
Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger • Foundations and Trends® in Computer Graphics and Vision
(2020)
Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the fiel...
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Open Access
DOI: https://doi.org/10.1561/0600000079
Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing
(2020)
A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...
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DOI: https://doi.org/10.3390/rs12111729
Licheng Jiao, Fan Zhang, Fang Liu, Shuyuan Yang et al. • IEEE Access
(2019)
Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in people’s life, such as monitoring security, autonomous driving and so on, with the purpose of locating instances of ...
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DOI: https://doi.org/10.1109/access.2019.2939201
Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, Alexander J. McKeeken et al. • Methods in Ecology and Evolution
(2022)
Abstract Deep learning is driving recent advances behind many everyday technologies, including speech and image recognition, natural language processing and autonomous driving. It is also gaining popularity in biology, where it has been use...
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DOI: https://doi.org/10.1111/2041-210x.13901