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E2ETrADS: end-to-end transformer based autonomous driving system for adverse weather conditions

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...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12544-026-00793-6

Performance Benchmarking: Pre-trained Models and Custom Convolutional Neural Networks in Deep Learning

Sheemona Joseph C., S. Ganesh, S. Kannadhasan, K. Selvipriya • Journal of Informatics and Web Engineering (2025)

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffic signs—a crucial ta...

DOAJ Open Access (DOAJ) DOI: 10.33093/jiwe.2025.4.2.14

Vision-Based Autonomous Landing of a Quadrotor on the Perturbed Deck of an Unmanned Surface Vehicle

Riccardo Polvara, Sanjay Sharma, Jian Wan, Andrew Manning et al. • Drones (2018)

Autonomous landing on the deck of an unmanned surface vehicle (USV) is still a major challenge for unmanned aerial vehicles (UAVs). In this paper, a fiducial marker is located on the platform so as to facilitate the task since it is possibl...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones2020015