Zobrazeno 1 - 10
of 972
pro vyhledávání: '"SCHWARTZ, WILLIAM"'
Autor:
Kasım, Furkan, Boult, Terrance E., Mora, Rensso, Biesseck, Bernardo, Ribeiro, Rafael, Schlueter, Jan, Repák, Tomáš, Vareto, Rafael Henrique, Menotti, David, Schwartz, William Robson, Günther, Manuel
In the current landscape of biometrics and surveillance, the ability to accurately recognize faces in uncontrolled settings is paramount. The Watchlist Challenge addresses this critical need by focusing on face detection and open-set identification i
Externí odkaz:
http://arxiv.org/abs/2409.07220
Autor:
Nascimento, Valfride, Laroca, Rayson, Ribeiro, Rafael O., Schwartz, William Robson, Menotti, David
Despite significant advancements in License Plate Recognition (LPR) through deep learning, most improvements rely on high-resolution images with clear characters. This scenario does not reflect real-world conditions where traffic surveillance often c
Externí odkaz:
http://arxiv.org/abs/2408.15103
Autor:
Sena, Jessica, Mostafiz, Mohammad Tahsin, Zhang, Jiaqing, Davidson, Andrea, Bandyopadhyay, Sabyasachi, Yuanfang, Ren, Ozrazgat-Baslanti, Tezcan, Shickel, Benjamin, Loftus, Tyler, Schwartz, William Robson, Bihorac, Azra, Rashidi, Parisa
Acuity assessments are vital in critical care settings to provide timely interventions and fair resource allocation. Traditional acuity scores rely on manual assessments and documentation of physiological states, which can be time-consuming, intermit
Externí odkaz:
http://arxiv.org/abs/2311.02251
Autor:
Vareto, Rafael Henrique, Linghu, Yu, Boult, Terrance E., Schwartz, William Robson, Günther, Manuel
Open-set face recognition characterizes a scenario where unknown individuals, unseen during the training and enrollment stages, appear on operation time. This work concentrates on watchlists, an open-set task that is expected to operate at a low Fals
Externí odkaz:
http://arxiv.org/abs/2311.00400
Publikováno v:
36th Conference on Graphics, Patterns and Images (SIBGRAPI 2023)
Open-set face recognition refers to a scenario in which biometric systems have incomplete knowledge of all existing subjects. Therefore, they are expected to prevent face samples of unregistered subjects from being identified as previously enrolled i
Externí odkaz:
http://arxiv.org/abs/2308.12371
Open-set face recognition describes a scenario where unknown subjects, unseen during the training stage, appear on test time. Not only it requires methods that accurately identify individuals of interest, but also demands approaches that effectively
Externí odkaz:
http://arxiv.org/abs/2308.07445
Autor:
Nascimento, Valfride, Laroca, Rayson, Lambert, Jorge de A., Schwartz, William Robson, Menotti, David
Publikováno v:
Computers & Graphics, vol. 113, pp. 69-76, 2023
Recent years have seen significant developments in the field of License Plate Recognition (LPR) through the integration of deep learning techniques and the increasing availability of training data. Nevertheless, reconstructing license plates (LPs) fr
Externí odkaz:
http://arxiv.org/abs/2305.17313
Autor:
Nascimento, Valfride, Laroca, Rayson, Lambert, Jorge de A., Schwartz, William Robson, Menotti, David
The License Plate Recognition (LPR) field has made impressive advances in the last decade due to novel deep learning approaches combined with the increased availability of training data. However, it still has some open issues, especially when the dat
Externí odkaz:
http://arxiv.org/abs/2210.16836
Autor:
Monteiro, Bruno A.A., Canguçu, Gabriel L., Jorge, Leonardo M.S., Vareto, Rafael H., Oliveira, Bryan S., Silva, Thales H., Lima, Luiz Alberto, Machado, Alexei M.C., Schwartz, William Robson, Vaz-de-Melo, Pedro O.S.
Publikováno v:
In Earth-Science Reviews November 2024 258
