ON THE ASSESSMENT OF INSTANCE SEGMENTATION FOR THE AUTOMATIC DETECTION OF SPECIFIC CONSTRUCTIONS FROM VERY HIGH RESOLUTION AIRBORNE IMAGERY

Autor: P. Achanccaray, M. Gerke, L. Wesche, S. Hoyer, K. Thiele, U. Knufinke, C. Krafczyk

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-1-W2-2023, Pp 1303-1309 (2023)

During the High Modernism period spanning from approximately 1914 to 1970, the manufacturing of steel-constructed system halls witnessed a significant surge to accommodate the growing demand across various sectors such as industry, commerce, and agri

Externí odkaz: https://doaj.org/article/574c2d9aa2784152bc1c6f10ca8d5a33

LEM BENCHMARK DATABASE FOR TROPICAL AGRICULTURAL REMOTE SENSING APPLICATION

Autor: I. D. Sanches, R. Q. Feitosa, P. Achanccaray, B. Montibeller, A. J. B. Luiz, M. D. Soares, V. H. R. Prudente, D. C. Vieira, L. E. P. Maurano

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-1, Pp 387-392 (2018)

The monitoring of agricultural activities at a regular basis is crucial to assure that the food production meets the world population demands, which is increasing yearly. Such information can be derived from remote sensing data. In spite of topic’s

Externí odkaz: https://doaj.org/article/8afaf08846df4e5a909180c841ed7ccb

A free web service for fast COVID-19 classification of chest X-Ray images

Autor: Castro, Jose David Bermudez, Rei, Ricardo, Ruiz, Jose E., Diaz, Pedro Achanccaray, Canchumuni, Smith Arauco, Villalobos, Cristian Muñoz, Coelho, Felipe Borges, Mendoza, Leonardo Forero, Pacheco, Marco Aurelio C.

The coronavirus outbreak became a major concern for society worldwide. Technological innovation and ingenuity are essential to fight COVID-19 pandemic and bring us one step closer to overcome it. Researchers over the world are working actively to fin

Externí odkaz: http://arxiv.org/abs/2009.01657

Deep Adversarial Domain Adaptation With Few-Shot Learning for Motor-Imagery Brain-Computer Interface

Autor: Chatrin Phunruangsakao, David Achanccaray, Mitsuhiro Hayashibe

Publikováno v: IEEE Access, Vol 10, Pp 57255-57265 (2022)

Electroencephalography (EEG) is the most prevalent signal acquisition technique for brain-computer interface (BCI). However, the statistical distribution of EEG data varies across subjects and sessions, resulting in poor generalization of the domain-

Externí odkaz: https://doaj.org/article/42fd81e5cdce4c7b83e3fcfb216b317b

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