Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Theus H. Aspiras"'
Autor:
Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus H. Aspiras
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 112, Iss , Pp 102921- (2022)
In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding.
Externí odkaz:
https://doaj.org/article/363830a9e20a46509b0057961257da5a
Autor:
Theus H. Aspiras, Vijayan K. Asari, Nina Singer, Jonathan Schierl, Andy Stokes, Brett Keaffaber, Andre Van Rynbach, Kevin Decker, David Rabb
Publikováno v:
Pattern Recognition and Tracking XXXIII.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::945bfb737c83898944597009146eaaa9
https://doi.org/10.1117/12.2622313
https://doi.org/10.1117/12.2622313
Publikováno v:
Pattern Recognition and Tracking XXXIII.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a49605d5247e8a23e64e4895e2b66f2
https://doi.org/10.1117/12.2622314
https://doi.org/10.1117/12.2622314
Publikováno v:
Pattern Recognition and Tracking XXXIII.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c36d13e34174be7670782aa07d856212
https://doi.org/10.1117/12.2622315
https://doi.org/10.1117/12.2622315
Publikováno v:
IEEE Access, Vol 8, Pp 68695-68710 (2020)
Mitotic cell detection is one of the challenging problems in the field of computational pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic markers for breast cancer diagnosis. The clinical visual inspection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6bdd175165a6ef2c7bf0499f2f18bd88
https://doi.org/10.1109/access.2020.2983995
https://doi.org/10.1109/access.2020.2983995
Publikováno v:
Pattern Recognition and Tracking XXXII.
Aerial object detection is one of the most important applications in computer vision. We propose a deep learning strategy for detection and classification of objects on the pipeline right of ways by analyzing aerial images captured by flying aircraft
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96dc3c84769d9612abeb0976d9b7f9da
https://doi.org/10.1117/12.2591194
https://doi.org/10.1117/12.2591194
Autor:
Quinn Graehling, Theus H. Aspiras, Dave Rabb, Vijay Asari, Jonathan Schierl, Andre Van Rynbach
Publikováno v:
AIPR
Multi-modal data is useful for complex imaging scenarios due to the exclusivity of information found in each modality, but there is a lack of meaningful comparisons of different modalities for object detection. In our work, we propose three contribut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56cc7df2eb2e0dd83572f8690e6687cc
https://doi.org/10.1109/aipr50011.2020.9425039
https://doi.org/10.1109/aipr50011.2020.9425039
Publikováno v:
Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications.
In the last few years, Deep Learning (DL) has been showing superior performance in different modalities of bio-medical image analysis. Several DL architectures have been proposed for classification, segmentation, and detection tasks in medical imagin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8fb0c14fbc9143f3909aeafdd0fe008
https://doi.org/10.1117/12.2550146
https://doi.org/10.1117/12.2550146
Publikováno v:
Optics & Laser Technology. 95:133-146
Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::281d14f3c661fd7c3cba1a669eeceb79
https://doi.org/10.1016/j.optlastec.2017.04.011
https://doi.org/10.1016/j.optlastec.2017.04.011
Autor:
Theus H. Aspiras, Vijayan K. Asari
Publikováno v:
Neurocomputing. 222:1-10
Extensive research and evaluations have been conducted on neural networks to improve classification accuracy and training time. Many classical architectures of neural networks have been modified in several different ways for advancement in design. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e704b9312dc04efa99ad961b468ac455
https://doi.org/10.1016/j.neucom.2016.10.002
https://doi.org/10.1016/j.neucom.2016.10.002