Zobrazeno 1 - 10
of 1 037
pro vyhledávání: '"Walsh, Joseph"'
Autor:
Walsh, Joseph B., Brown, Stephen R.
We consider a variation of Griffith's analysis of rupture, one which simulates the process of hydrofracturing, where fluid forced into a crack raises the fluid pressure until the crack begins to grow. Unlike that of Griffith, in this analysis fluid p
Externí odkaz:
http://arxiv.org/abs/2211.04221
Publikováno v:
Sensors and Transducers ISSN 2306-8515 e-ISSN 1726-5479 vol 252 pp 50-57 2021
Fine-Grained Change Detection and Regression Analysis are essential in many applications of ArtificialIntelligence. In practice, this task is often challenging owing to the lack of reliable ground truth information andcomplexity arising from interact
Externí odkaz:
http://arxiv.org/abs/2208.05800
Autor:
Mahony, Niall O', Campbell, Sean, Carvalho, Anderson, Krpalkova, Lenka, Velasco-Hernandez, Gustavo, Riordan, Daniel, Walsh, Joseph
Publikováno v:
Proceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 1, B. R. Arai K., Kapoor S., Ed. Springer, Cham, 2020, pp. 97 to 113
Deep Metric Learning (DML) approaches learn to represent inputs to a lower-dimensional latent space such that the distance between representations in this space corresponds with a predefined notion of similarity. This paper investigates how the mappi
Externí odkaz:
http://arxiv.org/abs/2009.03820
Autor:
Myers, Kyle R., Tham, Wei Yang, Yin, Yian, Cohodes, Nina, Thursby, Jerry G., Thursby, Marie C., Schiffer, Peter E., Walsh, Joseph T., Lakhani, Karim R., Wang, Dashun
The COVID-19 pandemic has undoubtedly disrupted the scientific enterprise, but we lack empirical evidence on the nature and magnitude of these disruptions. Here we report the results of a survey of approximately 4,500 Principal Investigators (PIs) at
Externí odkaz:
http://arxiv.org/abs/2005.11358
Autor:
Mahony, Niall O', Campbell, Sean, Carvalho, Anderson, Harapanahalli, Suman, Velasco-Hernandez, Gustavo, Krpalkova, Lenka, Riordan, Daniel, Walsh, Joseph
Publikováno v:
in Advances in Computer Vision Proceedings of the 2019 Computer Vision Conference (CVC). Springer Nature Switzerland AG, pp. 128-144
Deep Learning has pushed the limits of what was possible in the domain of Digital Image Processing. However, that is not to say that the traditional computer vision techniques which had been undergoing progressive development in years prior to the ri
Externí odkaz:
http://arxiv.org/abs/1910.13796