Enhancing rangeland weed detection through convolutional neural networks and transfer learning
Crop DesignThe detection of weed species in rangeland environments is a challenging task due to various factors such as dense, variable species vegetation, ocular occlusion, and a wide variety of plant morphology.
Christian Shackleton +2 more
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Comparing the Effectiveness of Classic Mask Rcnn and Vision Transformer in Early Weed Detection
, 2023 Shahnawaz Qureshi +4 more
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RCA-based Detection of Begomoviruses in Weed Genera Associated with Legumes in Southern Karnataka [PDF]
, 2021 Sudeep Pandey +4 more
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Remote Aerial Vehicle Solutions for Weed Detection in Precision Agriculture
IEEE AccessThis study presents a novel Remote Aerial Vehicle-based approach for detecting pigweeds in soybean (Glycine max) fields using a combination of deep learning and advanced image processing techniques.
Shekhar S. Borah +4 more
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Use of Blue-Green Fluorescence and Thermal Imaging in the Early Detection of Sunflower Infection by the Root Parasitic Weed Orobanche cumana Wallr. [PDF]
, 2017 Carmen M. Ortiz-Bustos +3 more
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Artificial Intelligence in AgricultureEffective weed management plays a critical role in enhancing the productivity and sustainability of cotton cultivation. The rapid emergence of herbicide-resistant weeds has underscored the need for innovative solutions to address the challenges ...
Ameer Tamoor Khan +2 more
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A comprehensive survey on weed and crop classification using machine learning and deep learning
Artificial Intelligence in AgricultureMachine learning and deep learning are subsets of Artificial Intelligence that have revolutionized object detection and classification in images or videos. This technology plays a crucial role in facilitating the transition from conventional to precision
Faisal Dharma Adhinata +2 more
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Detection of weeds in vegetables using image classification neural networks and image processing
Frontiers in PhysicsWeed management presents a major challenge to vegetable growth. Accurate identification of weeds is essential for automated weeding. However, the wide variety of weed types and their complex distribution creates difficulties in rapid and accurate weed ...
Huiping Jin +5 more
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Weed detection in soybean fields using improved YOLOv7 and evaluating herbicide reduction efficacy. [PDF]
Front Plant Sci, 2023 Li J, Zhang W, Zhou H, Yu C, Li Q.
europepmc +1 more source