Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Dias, Philipe A."'
Autor:
Dias, Philipe, Tsaris, Aristeidis, Bowman, Jordan, Potnis, Abhishek, Arndt, Jacob, Yang, H. Lexie, Lunga, Dalton
Publikováno v:
The 32nd ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL 24), October 29-November 1, 2024, Atlanta, GA, USA. ACM, New York, NY, USA, 4 pages
While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to billions of parameters has been shown to yield unprecedented benefits inc
Externí odkaz:
http://arxiv.org/abs/2410.19965
Autor:
Tsaris, Aristeidis, Dias, Philipe Ambrozio, Potnis, Abhishek, Yin, Junqi, Wang, Feiyi, Lunga, Dalton
As AI workloads increase in scope, generalization capability becomes challenging for small task-specific models and their demand for large amounts of labeled training samples increases. On the contrary, Foundation Models (FMs) are trained with intern
Externí odkaz:
http://arxiv.org/abs/2404.11706
Autor:
Dias, Philipe A., Medeiros, Henry
Semantic segmentation with fine-grained pixel-level accuracy is a fundamental component of a variety of computer vision applications. However, despite the large improvements provided by recent advances in the architectures of convolutional neural net
Externí odkaz:
http://arxiv.org/abs/2005.05856
Effective assisted living environments must be able to perform inferences on how their occupants interact with one another as well as with surrounding objects. To accomplish this goal using a vision-based automated approach, multiple tasks such as po
Externí odkaz:
http://arxiv.org/abs/1909.09225
Publikováno v:
2019 IEEE Winter Conference on Applications of Computer Vision (WACV)
Large-scale annotation of image segmentation datasets is often prohibitively expensive, as it usually requires a huge number of worker hours to obtain high-quality results. Abundant and reliable data has been, however, crucial for the advances on ima
Externí odkaz:
http://arxiv.org/abs/1902.06806
Akademický článek
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Publikováno v:
IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3003-3010, Oct. 2018
In fruit production, critical crop management decisions are guided by bloom intensity, i.e., the number of flowers present in an orchard. Despite its importance, bloom intensity is still typically estimated by means of human visual inspection. Existi
Externí odkaz:
http://arxiv.org/abs/1809.10080
Publikováno v:
Computers in Industry, vol. 99, pp. 17-28, Aug. 2018
To optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity, i.e., the number of flowers present in the orchard. Se
Externí odkaz:
http://arxiv.org/abs/1809.06357
Autor:
Dias, Philipe A., Medeiros, Henry
Despite recent improvements using fully convolutional networks, in general, the segmentation produced by most state-of-the-art semantic segmentation methods does not show satisfactory adherence to the object boundaries. We propose a method to refine
Externí odkaz:
http://arxiv.org/abs/1802.07789
Akademický článek
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