Zobrazeno 1 - 10
of 411
pro vyhledávání: '"Manso Luis"'
In the domain of multi-baseline stereo, the conventional understanding is that, in general, increasing baseline separation substantially enhances the accuracy of depth estimation. However, prevailing self-supervised depth estimation architectures pri
Externí odkaz:
http://arxiv.org/abs/2407.20437
Traffic congestion in urban areas presents significant challenges, and Intelligent Transportation Systems (ITS) have sought to address these via automated and adaptive controls. However, these systems often struggle to transfer simulated experiences
Externí odkaz:
http://arxiv.org/abs/2312.05031
Autor:
Singamaneni, Phani Teja, Bachiller-Burgos, Pilar, Manso, Luis J., Garrell, Anaís, Sanfeliu, Alberto, Spalanzani, Anne, Alami, Rachid
Socially aware robot navigation is gaining popularity with the increase in delivery and assistive robots. The research is further fueled by a need for socially aware navigation skills in autonomous vehicles to move safely and appropriately in spaces
Externí odkaz:
http://arxiv.org/abs/2311.06922
Current, self-supervised depth estimation architectures rely on clear and sunny weather scenes to train deep neural networks. However, in many locations, this assumption is too strong. For example in the UK (2021), 149 days consisted of rain. For the
Externí odkaz:
http://arxiv.org/abs/2307.08357
Autor:
Francis, Anthony, Pérez-D'Arpino, Claudia, Li, Chengshu, Xia, Fei, Alahi, Alexandre, Alami, Rachid, Bera, Aniket, Biswas, Abhijat, Biswas, Joydeep, Chandra, Rohan, Chiang, Hao-Tien Lewis, Everett, Michael, Ha, Sehoon, Hart, Justin, How, Jonathan P., Karnan, Haresh, Lee, Tsang-Wei Edward, Manso, Luis J., Mirksy, Reuth, Pirk, Sören, Singamaneni, Phani Teja, Stone, Peter, Taylor, Ada V., Trautman, Peter, Tsoi, Nathan, Vázquez, Marynel, Xiao, Xuesu, Xu, Peng, Yokoyama, Naoki, Toshev, Alexander, Martín-Martín, Roberto
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation of algori
Externí odkaz:
http://arxiv.org/abs/2306.16740
It is essential for autonomous robots to be socially compliant while navigating in human-populated environments. Machine Learning and, especially, Deep Reinforcement Learning have recently gained considerable traction in the field of Social Navigatio
Externí odkaz:
http://arxiv.org/abs/2304.14102
Publikováno v:
Machine Vision and Applications 35, 46 (2024)
Its numerous applications make multi-human 3D pose estimation a remarkably impactful area of research. Nevertheless, assuming a multiple-view system composed of several regular RGB cameras, 3D multi-pose estimation presents several challenges. First
Externí odkaz:
http://arxiv.org/abs/2212.08731
Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent work focuses on improving depth estimation by increasing architecture c
Externí odkaz:
http://arxiv.org/abs/2206.03799
Autor:
Zola, Paolo, Casanova, Claudia, Arcangeli, Valentina, Antonuzzo, Lorenzo, Gadducci, Angiolo, Cosio, Stefania, Clamp, Andrew, Persic, Mojca, McNeish, Ian, Tookman, Laura, Redondo Sanchez, Andrés, Choi, Chel Hun, Baldini, Editta, Palaia, Innocenza, Benedetti Panici, Pierluigi, Takahashi, Nobutaka, Lombard, Janine, Ardizzoia, Antonio, Bologna, Alessandra, Herrero Ibáñez, Ana Maria, Musolino, Antonino, Márquez Vázquez, Raúl, Pietzner, Klaus, Braicu, Elena, Heinzelmann-Schwarz, Viola A., Powell, Melanie, Yokoyama, Yoshihito, Baron-Hay, Sally, Abeni, Chiara, Martin Lorente, Cristina, Cueva, Juan Fernando, Trillsch, Fabian, Heitz, Florian, Ataseven, Beyhan, Petru, Edgar, Heubner, MartinLeonhard, Sadozye, Azmat Hassanq, Dubey, Sidharth, Tazbirkova, Andrea, Tiley, Susan, Chrystal, Kathryn, Kim, Sang Wun, Fehr, Mathias, Scatchard, Kate, Anand, Anjana, Taylor, Alexandra, Watary, Hidemichi, Enomoto, Takayuki, Yoshihara, Kosuke, Selva-Nayagam, Sudarsha, Karki, Bhaskar, Harrison, Michelle, Wilkinson, Kate, Goh, Jeffrey, Glasgow, Amanda, Chantrill, Lorraine, Lee, Chulmin, Bertolini, Alessandro, Narducci, Filomena, Bellotti, Giovanna, Fusco, Vittorio, Aebi, Stefan, Del Grande, Maria, Colombo, Ilaria, Tokunaga, Hideki, Shigeta, Shogo, Goss, Geraldine, Siow, Zhen Rong, Steer, Christopher, Lin, Hao, Lee, Kwang-Beom, Di Meglio, Giovanni, Massa, Elena, De Marino, Elvira, Tortora, Vincenzo, Palacio Vazquez, Isabel, Tsuji, Kosuke, Tominaga, Eiichiro, Black, Allison, So, Kyeong A, Suh, Dong Hoon, Lee, Keun Ho, Kim, Yong Man, Fossati, Roldano, Carlucci, Luciano, Barberis, Massimo, Torri, Valter, Santoni, Anna, Colombo, Nicoletta, Biagioli, Elena *, Harano, Kenichi, Galli, Francesca, Hudson, Emma, Antill, Yoland, Rabaglio, Manuela, Marmé, Frederic, Marth, Christian, Parma, Gabriella, Fariñas-Madrid, Lorena, Nishio, Shin, Allan, Karen, Lee, Yeh Chen, Piovano, Elisa, Pardo, Beatriz, Nakagawa, Satoshi, McQueen, John, Zamagni, Claudio, Manso, Luis, Takehara, Kazuhiro, Tasca, Giulia, Ferrero, Annamaria, Tognon, Germana, Lissoni, Andrea Alberto, Petrella, Mariacristina, Laudani, Maria Elena, Rulli, Eliana, Uggeri, Sara, Barretina Ginesta, M Pilar
Publikováno v:
In The Lancet Oncology September 2024 25(9):1135-1146
Contemporary Artificial Intelligence technologies allow for the employment of Computer Vision to discern good crops from bad, providing a step in the pipeline of selecting healthy fruit from undesirable fruit, such as those which are mouldy or gangre
Externí odkaz:
http://arxiv.org/abs/2104.05647