Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Zhongqi Miao"'
Autor:
Zhongqi Miao, Stella X. Yu, Kyle L. Landolt, Mark D. Koneff, Timothy P. White, Luke J. Fara, Enrika J. Hlavacek, Bradley A. Pickens, Travis J. Harrison, Wayne M. Getz
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 9, Iss 4, Pp 439-453 (2023)
Abstract Remote aerial sensing provides a non‐invasive, large geographical‐scale technology for avian monitoring, but the manual processing of images limits its development and applications. Artificial Intelligence (AI) methods can be used to mit
Externí odkaz:
https://doaj.org/article/768e099f37754c19afd064e0a40dc959
Autor:
Zhongqi Miao, Wenxuan Huang
Publikováno v:
Systems Science & Control Engineering, Vol 10, Iss 1, Pp 653-661 (2022)
Aiming at the portfolio problem of gold and bitcoin with a given linear trading commission, this paper puts forward the stage implementation forecast and optimal portfolio model. In the aspect of data prediction, SMA is used to predict the initial da
Externí odkaz:
https://doaj.org/article/5a7b51ddc9474c0faade768a2a71914e
Autor:
Ludovica Luisa Vissat, Nir Horvitz, Rachael V. Phillips, Zhongqi Miao, Whitney Mgbara, Yue You, Richard Salter, Alan E. Hubbard, Wayne M. Getz
Publikováno v:
Epidemics, Vol 41, Iss , Pp 100640- (2022)
We investigated the initial outbreak rates and subsequent social distancing behaviour over the initial phase of the COVID-19 pandemic across 29 Combined Statistical Areas (CSAs) of the United States. We used the Numerus Model Builder Data and Simulat
Externí odkaz:
https://doaj.org/article/c9f5ed30186d4a9ca39044ac8d3c6e94
Publikováno v:
IEEE Signal Processing Letters. :1-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb4c3bac5067bce3478ebd02fab7dc75
https://doi.org/10.1109/lsp.2023.3257725
https://doi.org/10.1109/lsp.2023.3257725
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. :1-15
Real world data often exhibits a long-tailed and open-ended (with unseen classes) distribution. A practical recognition system must balance between majority (head) and minority (tail) classes, generalize across the distribution, and acknowledge novel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d19b3b567492d8a41a779e9ca96e109
https://doi.org/10.1109/tpami.2022.3200091
https://doi.org/10.1109/tpami.2022.3200091
Publikováno v:
Nature Machine Intelligence. 3:885-895
Camera trapping is increasingly used to monitor wildlife, but this technology typically requires extensive data annotation. Recently, deep learning has significantly advanced automatic wildlife recognition. However, current methods are hampered by a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d178bd26f20689fd44e1e3752ddfa858
https://doi.org/10.1038/s42256-021-00393-0
https://doi.org/10.1038/s42256-021-00393-0
Publikováno v:
CVPR
A typical domain adaptation approach is to adapt models trained on the annotated data in a source domain (e.g., sunny weather) for achieving high performance on the test data in a target domain (e.g., rainy weather). Whether the target contains a sin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::900082f90477926f106ec103604357d6
Publikováno v:
CVPR
Real world data often have a long-tailed and open-ended distribution. A practical recognition system must classify among majority and minority classes, generalize from a few known instances, and acknowledge novelty upon a never seen instance. We defi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f79d748863f27c17e75b3cdefa0e742
Autor:
Graeme S. Cumming, Nyeema C. Harris, Hyun S. Yoon, Tad A. Dallas, Oliver Muellerklein, Kevin R. Burgio, Carrie A. Cizauskas, Castaldo G, Wayne M. Getz, Zhongqi Miao, Heather C. Proctor, Jorge Doña, Colin J. Carlson, Anna J. Phillips, Roger Jovani
Parasite conservation is a rapidly growing field at the intersection of ecology, epidemiology, parasitology, and public health. The overwhelming diversity of parasitic life on earth, and recent work showing that parasites and other symbionts face sev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecf562508ee1e85a0e2c33c23563d9b8