Zobrazeno 1 - 10
of 182
pro vyhledávání: '"William Robson Schwartz"'
Autor:
Jessica Sena, Mohammad Tahsin Mostafiz, Jiaqing Zhang, Andrea E. Davidson, Sabyasachi Bandyopadhyay, Subhash Nerella, Yuanfang Ren, Tezcan Ozrazgat-Baslanti, Benjamin Shickel, Tyler Loftus, William Robson Schwartz, Azra Bihorac, Parisa Rashidi
Publikováno v:
Frontiers in Neurology, Vol 15 (2024)
Acuity assessments are vital for timely interventions and fair resource allocation in critical care settings. Conventional acuity scoring systems heavily depend on subjective patient assessments, leaving room for implicit bias and errors. These asses
Externí odkaz:
https://doaj.org/article/c9165c11d45b47dcb5b1d0b3119bc324
Autor:
Rayson Laroca, Luiz A. Zanlorensi, Gabriel R. Gonçalves, Eduardo Todt, William Robson Schwartz, David Menotti
Publikováno v:
IET Intelligent Transport Systems, Vol 15, Iss 4, Pp 483-503 (2021)
Abstract This paper presents an efficient and layout‐independent Automatic License Plate Recognition (ALPR) system based on the state‐of‐the‐art you only look once (YOLO) object detector that contains a unified approach for license plate (LP)
Externí odkaz:
https://doaj.org/article/93c7822c890044a8a339ba733693a522
Autor:
Valfride Nascimento, Rayson Laroca, Jorge de A. Lambert, William Robson Schwartz, David Menotti
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea57bfb8d13a07f1703eadbc5fee2644
Publikováno v:
2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb16df503aa0e9363b1e9a613dd0840a
https://doi.org/10.1109/sibgrapi55357.2022.9991762
https://doi.org/10.1109/sibgrapi55357.2022.9991762
Publikováno v:
Neurocomputing. 444:226-243
Sensor-based Human Activity Recognition (sensor-based HAR) has been used in many real-world applications providing valuable knowledge to many areas, such as human-object interaction, medical, military and security. Recently, wearable devices have pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e829f23e607c08e99255e69c7ff97a33
https://doi.org/10.1016/j.neucom.2020.04.151
https://doi.org/10.1016/j.neucom.2020.04.151
Autor:
David Menotti, Eduardo Todt, William Robson Schwartz, Gabriel Resende Gonçalves, Rayson Laroca, Luiz A. Zanlorensi
Publikováno v:
IET Intelligent Transport Systems, Vol 15, Iss 4, Pp 483-503 (2021)
This paper presents an efficient and layout‐independent Automatic License Plate Recognition (ALPR) system based on the state‐of‐the‐art you only look once (YOLO) object detector that contains a unified approach for license plate (LP) detectio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f75e4dc400d194e0ff2bd03ad0158ece
https://doaj.org/article/93c7822c890044a8a339ba733693a522
https://doaj.org/article/93c7822c890044a8a339ba733693a522
Publikováno v:
Pattern Analysis and Applications. 24:511-521
Facial biometrics tend to be spontaneous, instinctive and less human intrusive. It is regularly employed in the authentication of authorized users and personnel to protect data from violation attacks. A face spoofing attack usually comprises the ille
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87f369d506772ba1a63acd9374bde21c
https://doi.org/10.1007/s10044-020-00937-x
https://doi.org/10.1007/s10044-020-00937-x
Publikováno v:
Pattern Analysis and Applications. 24:497-507
Gait is a biometry characterized by the identification of individuals by the way they walk. It is recently gaining evidence because it can be collected at distance and does not require subject cooperation, which is desirable on surveillance scenarios
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2a9d782ae8a68a1374c73d5d23833de
https://doi.org/10.1007/s10044-020-00935-z
https://doi.org/10.1007/s10044-020-00935-z
Publikováno v:
Neurocomputing. 406:234-243
Modern visual pattern recognition methods are based on convolutional networks since they are able to learn complex patterns directly from the data. However, convolutional networks are computationally expensive in terms of floating point operations (F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::100606643d6d66bd434dafe0d65c0d7f
https://doi.org/10.1016/j.neucom.2020.03.108
https://doi.org/10.1016/j.neucom.2020.03.108
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 14:828-837
The predictive ability of convolutional neural networks (CNNs) can be improved by increasing their depth. However, increasing depth also increases computational cost significantly, in terms of both floating point operations and memory consumption, hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cff54ceaaa4f4b00e7f0d84cd3a806c9
https://doi.org/10.1109/jstsp.2020.2975987
https://doi.org/10.1109/jstsp.2020.2975987