Big data management algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the internet of robotic …

M Andronie, G Lăzăroiu, M Iatagan, I Hurloiu… - … International Journal of …, 2023 - mdpi.com
The objective of this systematic review was to analyze the recently published literature on
the Internet of Robotic Things (IoRT) and integrate the insights it articulates on big data …

[HTML][HTML] Artificial intelligence for environmental security: national, international, human and ecological perspectives

M Francisco - Current Opinion in Environmental Sustainability, 2023 - Elsevier
Highlights•Environmental security perspectives can shape our understanding of artificial
intelligence.•These perspectives impact the aims, uses, actors nvolved, risks and …

Autonomous, onboard vision-based trash and litter detection in low altitude aerial images collected by an unmanned aerial vehicle

M Kraft, M Piechocki, B Ptak, K Walas - Remote Sensing, 2021 - mdpi.com
Public littering and discarded trash are, despite the effort being put to limit it, still a serious
ecological, aesthetic, and social problem. The problematic waste is usually localised and …

[HTML][HTML] A citizen science unmanned aerial system data acquisition protocol and deep learning techniques for the automatic detection and mapping of marine litter …

A Papakonstantinou, M Batsaris, S Spondylidis… - Drones, 2021 - mdpi.com
Marine litter (ML) accumulation in the coastal zone has been recognized as a major problem
in our time, as it can dramatically affect the environment, marine ecosystems, and coastal …

Artificial intelligence and public values: value impacts and governance in the public sector

YC Chen, MJ Ahn, YF Wang - Sustainability, 2023 - mdpi.com
While there has been growth in the literature exploring the governance of artificial
intelligence (AI) and recognition of the critical importance of guiding public values, the …

Using artificial intelligence to support marine macrolitter research: a content analysis and an online database

DV Politikos, A Adamopoulou, G Petasis… - Ocean & Coastal …, 2023 - Elsevier
Marine scientists use a variety of collection and monitoring methods to survey macrolitter in
aquatic environments, aiming to assess the level of pollution and design mitigation actions …

Pixel-level image classification for detecting beach litter using a deep learning approach

M Hidaka, D Matsuoka, D Sugiyama, K Murakami… - Marine Pollution …, 2022 - Elsevier
Mitigating and preventing beach litter from entering the ocean is urgently required.
Monitoring beach litter solely through human effort is cumbersome, with respect to both time …

Deep learning-driven surveillance quality enhancement for maritime management promotion under low-visibility weathers

J Qu, Y Gao, Y Lu, W Xu, RW Liu - Ocean & Coastal Management, 2023 - Elsevier
Visual sensors are widely employed for real-time maritime surveillance. But they always
suffer from some low-visibility problems, typically low light and haze, which greatly reduce …

Exploiting high-fidelity kinematic information from port surveillance videos via a YOLO-based framework

X Xu, X Chen, B Wu, Z Wang, J Zhen - Ocean & Coastal Management, 2022 - Elsevier
Port surveillance videos provide rich and intuitive temporal and spatial information and
motion information, which is conducive to path planning, obstacle avoidance and …

[PDF][PDF] Integrating artificial intelligence in cyber security for cyber-physical systems

M Alowaidi, SK Sharma, A AlEnizi… - Electronic Research …, 2023 - aimspress.com
Due to the complexities of systems thinking and the communication between independent
Cyber-Physical Systems (CPSs) areas through accumulative expansion, several security …