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Photogrammetric determination of movement speed of invasive Indo-Pacific lionfish in the Florida Keys.
PeerJ
January 2025
Department of Oceanography and Coastal Sciences, Louisiana State University and Agricultural and Mechanical College, Baton Rouge, LA, United States of America.
As a key determinant of how efficiently lionfish ( sp.) locate and capture prey, swimming speed plays a crucial role in shaping the predator-prey interactions and broader ecological dynamics within the invaded ecosystems. Swimming speed on a small temporal and spatial scale is difficult to measure because of the need for precise measurements of both distance and duration of the behavior.
View Article and Find Full Text PDFA customized convolutional neural network-based approach for weeds identification in cotton crops.
Front Plant Sci
January 2025
Information and Communication Engineering, Yeungnam University, Gyeongsan, Republic of Korea.
Smart farming is a hot research area for experts globally to fulfill the soaring demand for food. Automated approaches, based on convolutional neural networks (CNN), for crop disease identification, weed classification, and monitoring have substantially helped increase crop yields. Plant diseases and pests are posing a significant danger to the health of plants, thus causing a reduction in crop production.
View Article and Find Full Text PDFDrone imagery dataset for early-season weed classification in maize and tomato crops.
Data Brief
February 2025
Institute of Agricultural Sciences, Spanish National Research Council (ICA-CSIC), Serrano 115b, 28006 Madrid, Spain.
Identifying weed species at early-growth stages is critical for precision agriculture. Accurate classification at the species-level enables targeted control measures, significantly reducing pesticide use. This paper presents a dataset of RGB images captured with a Sony ILCE-6300L camera mounted on an unmanned aerial vehicle (UAV) flying at an altitude of 11 m above ground level.
View Article and Find Full Text PDFRevolutionizing Diabetic Retinopathy Screening: Integrating AI-Based Retinal Imaging in Primary Care.
J CME
January 2025
DKBmed, New York, NY, USA.
Diabetic retinopathy (DR) is a public health issue affecting millions in the United States and Europe. However, despite strong recommendations for screening at regular intervals by many professional societies, including the American Diabetes Association and the American Academy of Ophthalmology, screening rates remain suboptimal, with only 50-70% of patients with diabetes adhering to recommended annual eye exams. Barriers to screening include lack of awareness, socioeconomic factors, health care system fragmentation, and workforce shortages, among others.
View Article and Find Full Text PDFCombined Barrier-Target Coverage for Directional Sensor Network.
Sensors (Basel)
December 2024
Széchenyi István University, 9026 Győr, Hungary.
Over the past twenty years, camera networks have become increasingly popular. In response to various demands imposed on these networks, several coverage models have been developed in the scientific literature, such as area, trap, barrier, and target coverage. In this paper, a new type of coverage task, the Maximum Target Coverage with k-Barrier Coverage (MTCBC-k) problem, is defined.
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