Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Fernando Hermosillo-Reynoso"'
Publikováno v:
Sensors, Vol 24, Iss 23, p 7463 (2024)
Since multi-view learning leverages complementary information from multiple feature sets to improve model performance, a tensor-based data fusion layer for neural networks, called Multi-View Data Tensor Fusion (MV-DTF), is used. It fuses M feature sp
Externí odkaz:
https://doaj.org/article/cb6815bf52f74fed9dee7465b6ca3e35
Publikováno v:
Entropy, Vol 20, Iss 10, p 725 (2018)
Lane detection for traffic surveillance in intelligent transportation systems is a challenge for vision-based systems. In this paper, a novel pixel-entropy based algorithm for the automatic detection of the number of lanes and their centers, as well
Externí odkaz:
https://doaj.org/article/6f867ac7b4974eeeb654e7f3a7a401cc
Autor:
Jayro Santiago-Paz, Julio César Ramírez-Pacheco, Deni Torres-Roman, Fernando Hermosillo-Reynoso
Publikováno v:
Entropy
Volume 20
Issue 10
Entropy, Vol 20, Iss 10, p 725 (2018)
Volume 20
Issue 10
Entropy, Vol 20, Iss 10, p 725 (2018)
Lane detection for traffic surveillance in intelligent transportation systems is a challenge for vision-based systems. In this paper, a novel pixel-entropy based algorithm for the automatic detection of the number of lanes and their centers, as well
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ca0fe7538af3df20dcdff8b68de9ba9
Autor:
Yuriy V. Shkvarko, David Gómez-Gutiérrez, Misael Romero-Delgado, Roxana Velazquez-Pupo, Fernando Hermosillo-Reynoso, Daniel Robles-Valdez, Jayro Santiago-Paz, Deni Torres-Roman, Alberto Sierra-Romero
Publikováno v:
Sensors; Volume 18; Issue 2; Pages: 374
Sensors (Basel, Switzerland)
Sensors (Basel, Switzerland)
This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c138f6671dc42ee101c86fedab69b1ec
https://doi.org/10.3390/s18020374
https://doi.org/10.3390/s18020374