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| Filter results3 paper(s) found. |
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1. Misalignment Between Sugar Cane Transshipment Trailers and TractorSugarcane production system is dependent on a continuous cutting and regrowth of cane plants from their roots, on which traffic should be avoided to ensure the physiological integrity of regrowth and productivity. This need for accuracy in sugarcane machine traffic boosted the adoption of automated steering systems, especially on harvesters. Tractors with the transshipment trailers, which continually accompany the harvesters in the field, yet do not adopt it or use technology with lower... B.P. Passalaqua, J. Molin, J. Salvi, A.P. Aguilera |
2. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and VisionAdvancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi |
3. Advanced Classification of Beetle Doppelgängers Using Siamese Neural Networks and Imaging TechniquesThe precise identification of beetle species, especially those that have similar macrostructure and physical characteristics, is a challenging task in the field of entomology. The term "Beetle Doppelgängers" refers to species that exhibit almost indistinguishable macrostructural characteristics, which can complicate tasks in ecological studies, conservation efforts, and pest management. The core issue resides in their striking similarity, frequently confusing both experts and automated... P.R. Armstrong, L.O. Pordesimo, K. Siliveru, A.R. Gerken, R.O. Serfa juan |