Zobrazeno 1 - 5
of 5
pro vyhledávání: '"S. K. Abhilash"'
Publikováno v:
IEEE Access, Vol 12, Pp 149162-149172 (2024)
In computer vision, semantic segmentation precisely delineates objects at the pixel level. This fundamental idea is constantly evolving by adding new modules and adjustments to suit the unique characteristics of different object classes. Pixel-level
Externí odkaz:
https://doaj.org/article/5fe665540d404201838b4d00dac2ecf1
Publikováno v:
IEEE Access, Vol 11, Pp 106749-106759 (2023)
Over the past few years, deep learning techniques have revolutionized the field of face parsing by utilizing massive datasets to generate high-level features and achieve outstanding performance. Usually, these techniques involve Convolutional Neural
Externí odkaz:
https://doaj.org/article/bb9d28ace5194bf9a79c0fea8c08e935
Publikováno v:
IEEE Access, Vol 11, Pp 83377-83389 (2023)
Amodal segmentation is a critical task in the field of computer vision as it involves accurately estimating object boundaries that extend beyond occlusion. This paper introduces a network named after the Amodal Segmentation Head, ASH-Net, a novel arc
Externí odkaz:
https://doaj.org/article/97c7ee806d3f4506b7d201c849015c97
Publikováno v:
IEEE Access, Vol 11, Pp 10881-10893 (2023)
Numerous deep perception technologies and methods are built on the foundation of pedestrian feature identification. It covers various fields, including autonomous driving, spying, and object tracking. A recent study area is the identification of pers
Externí odkaz:
https://doaj.org/article/9ce3e7a3ba434f98aa2cdc6d83e3755d
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811073854
Air pollution control measures in India are still in its infancy, while the country is developing at a faster rate. Development is known to affect the air quality of a place adversely. The key to manage the air quality of a place is proper planning,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc82761fe0141b70f4d08f3f39615ef6
https://doi.org/10.1007/978-981-10-7386-1_36
https://doi.org/10.1007/978-981-10-7386-1_36