Zobrazeno 1 - 10
of 216
pro vyhledávání: '"Melba M. Crawford"'
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
In both plant breeding and crop management, interpretability plays a crucial role in instilling trust in AI-driven approaches and enabling the provision of actionable insights. The primary objective of this research is to explore and evaluate the pot
Externí odkaz:
https://doaj.org/article/f4a74cd57dc547049f3dbd585a78a90a
Autor:
Jae‐In Kim, Junhwa Chi, Ali Masjedi, John Evan Flatt, Melba M. Crawford, Ayman F. Habib, Joohan Lee, Hyun‐Cheol Kim
Publikováno v:
Geoscience Data Journal, Vol 9, Iss 2, Pp 221-234 (2022)
Abstract Hyperspectral data are gaining popularity in remote sensing and signal processing communities because of the increased spectral information relative to multispectral data. Several airborne and spaceborne hyperspectral datasets are publicly a
Externí odkaz:
https://doaj.org/article/cee4c7e1d0c94bba97c827a79d29bda7
Autor:
Seth A. Tolley, Neal Carpenter, Melba M. Crawford, Edward J. Delp, Ayman Habib, Mitchell R. Tuinstra
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Remote sensing enables the rapid assessment of many traits that provide valuable information to plant breeders throughout the growing season to improve genetic gain. These traits are often extracted from remote sensing data on a row segment (rows wit
Externí odkaz:
https://doaj.org/article/bbd601ddd9104760bd5bf7d54840e3ee
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Yield for biofuel crops is measured in terms of biomass, so measurements throughout the growing season are crucial in breeding programs, yet traditionally time- and labor-consuming since they involve destructive sampling. Modern remote sensing platfo
Externí odkaz:
https://doaj.org/article/d514db01e61f43f6b4faec2a0dcfdaac
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 8085-8094 (2022)
Unmanned aerial vehicles (UAVs) equipped with lightweight sensors, such as RGB cameras and LiDAR, have significant potential in precision agriculture, including object detection. Tassel detection in maize is an essential trait given its relevance as
Externí odkaz:
https://doaj.org/article/33700e78b0c74380871837d63d82b570
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
Leaf area index (LAI) is an important variable for characterizing plant canopy in crop models. It is traditionally defined as the total one-sided leaf area per unit ground area and is estimated by both direct and indirect methods. This paper explores
Externí odkaz:
https://doaj.org/article/c711af355c074708851ede2fe36634a3
Publikováno v:
Remote Sensing, Vol 14, Iss 22, p 5884 (2022)
Overuse of nitrogen (N), an essential nutrient in food production systems, can lead to health issues and environmental degradation. Two parameters related to N efficiency, N Conversion Efficiency (NCE) and N Internal Efficiency (NIE), measure the amo
Externí odkaz:
https://doaj.org/article/92b81fcb0cdb4ad6aacb483e57967973
Publikováno v:
Remote Sensing, Vol 14, Iss 7, p 1721 (2022)
Enhancing the nitrogen (N) efficiency of maize hybrids is a common goal of researchers, but involves repeated field and laboratory measurements that are laborious and costly. Hyperspectral remote sensing has recently been investigated for measuring a
Externí odkaz:
https://doaj.org/article/3f6c6846bc99481d9dfee8a77db964b9
Publikováno v:
Remote Sensing, Vol 12, Iss 21, p 3587 (2020)
High-throughput phenotyping using high spatial, spectral, and temporal resolution remote sensing (RS) data has become a critical part of the plant breeding chain focused on reducing the time and cost of the selection process for the “best” genoty
Externí odkaz:
https://doaj.org/article/dfcf1d241b6e45bd8fcd3470c5b00214
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-16
Exploring fast and effective spectral-spatial feature extraction algorithms for hyperspectral image (HSI) classification is one of the most focus problems in current hyperspectral remote-sensing research. Generally, the size of homogeneous regions in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8ba2bb9599ce6123adceb1dd7f83116
https://doi.org/10.1109/tgrs.2021.3091860
https://doi.org/10.1109/tgrs.2021.3091860