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Abderrazzaq Kharroubi, Zouhair Ballouch, Rafika Hajji, Anass Yarroudh and Roland Billen
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations o...
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Salvatore Savastano, Paula Gomes da Silva, Jara Martínez Sánchez, Arnau Garcia Tort, Andres Payo, Mark E. Pattle, Albert Garcia-Mondéjar, Yeray Castillo and Xavier Monteys
Coasts are continually changing and remote sensing from satellites has the potential to both map and monitor coastal change at multiple scales. Unlike optical technology, synthetic aperture radar (SAR) is uninfluenced by darkness, clouds, and rain, poten...
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Liyana Wijayathunga, Alexander Rassau and Douglas Chai
The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relatively...
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Ranjini Surendran, Ines Chihi, J. Anitha and D. Jude Hemanth
Scene understanding is one of the most challenging areas of research in the fields of robotics and computer vision. Recognising indoor scenes is one of the research applications in the category of scene understanding that has gained attention in recent y...
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Songnan Chen, Mengxia Tang, Ruifang Dong and Jiangming Kan
The semantic segmentation of outdoor images is the cornerstone of scene understanding and plays a crucial role in the autonomous navigation of robots. Although RGB?D images can provide additional depth information for improving the performance of semanti...
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Abdullah Jan and Suyoung Seo
Depth maps are single image metrics that carry the information of a scene in three-dimensional axes. Accurate depth maps can recreate the 3D structure of a scene, which helps in understanding the full geometry of the objects within the scene. Depth maps ...
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Maryam Omar, Hafeez Ur Rehman, Omar Bin Samin, Moutaz Alazab, Gianfranco Politano and Alfredo Benso
Text-to-image synthesis is one of the most critical and challenging problems of generative modeling. It is of substantial importance in the area of automatic learning, especially for image creation, modification, analysis and optimization. A number of wo...
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Fariba Lotfi, Amin Beheshti, Helia Farhood, Matineh Pooshideh, Mansour Jamzad and Hamid Beigy
In our digital age, data are generated constantly from public and private sources, social media platforms, and the Internet of Things. A significant portion of this information comes in the form of unstructured images and videos, such as the 95 million d...
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Yaxuan Wang, Zhixin Zeng, Qiushan Li and Yingrui Deng
Urban-safety perception is crucial for urban planning and pedestrian street preference studies. With the development of deep learning and the availability of high-resolution street images, the use of artificial intelligence methods to deal with urban-saf...
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Gabriel Giraldo, Myriam Servières and Guillaume Moreau
Wind can influence people?s behavior and their way of inhabiting an architectural or urban space. Furthermore, virtual reality (VR) enables the simulation of different physical and sensitive phenomena such as the wind. We aim to analyze the effects of di...
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