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[HTML][HTML] Transforming weed management in sustainable agriculture with artificial intelligence: A systematic literature review towards weed identification and deep …
In the face of increasing agricultural demands and environmental concerns, the effective
management of weeds presents a pressing challenge in modern agriculture. Weeds not only …
management of weeds presents a pressing challenge in modern agriculture. Weeds not only …
[HTML][HTML] Early weed identification based on deep learning: A review
Weeds were one of the most destructive constraints on crop production and posed a
significant threat to agricultural productivity. The increasing development of smart agriculture …
significant threat to agricultural productivity. The increasing development of smart agriculture …
Evaluation of support vector machine and artificial neural networks in weed detection using shape features
Weed detection is still a challenging problem for robotic weed removal. Small tolerance
between the cutting tine and main crop position requires highly precise discrimination of the …
between the cutting tine and main crop position requires highly precise discrimination of the …
Weed25: A deep learning dataset for weed identification
P Wang, Y Tang, F Luo, L Wang, C Li, Q Niu… - Frontiers in Plant …, 2022 - frontiersin.org
Weed suppression is an important factor affecting crop yields. Precise identification of weed
species will contribute to automatic weeding by applying proper herbicides, hoeing position …
species will contribute to automatic weeding by applying proper herbicides, hoeing position …
Transfer learning for the classification of sugar beet and volunteer potato under field conditions
Highlights•Transfer learning provided very promising performance for weed/crop
classification.•The highest classification accuracy of 98.7% was obtained with VGG-19.•All …
classification.•The highest classification accuracy of 98.7% was obtained with VGG-19.•All …
A deep semantic segmentation-based algorithm to segment crops and weeds in agronomic color images
In precision agriculture, the accurate segmentation of crops and weeds in agronomic images
has always been the center of attention. Many methods have been proposed but still the …
has always been the center of attention. Many methods have been proposed but still the …
[HTML][HTML] Image patch-based deep learning approach for crop and weed recognition
Accurate classification of weed species in crop plants plays a crucial role in precision
agriculture by enabling targeted treatment. Recent studies show that artificial intelligence …
agriculture by enabling targeted treatment. Recent studies show that artificial intelligence …
[HTML][HTML] Deep learning-based object detection system for identifying weeds using uas imagery
Current methods of broadcast herbicide application cause a negative environmental and
economic impact. Computer vision methods, specifically those related to object detection …
economic impact. Computer vision methods, specifically those related to object detection …
In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation
In this paper, we present a challenging task of 3D segmentation of individual plant leaves
from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to …
from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to …
Potential use of ground‐based sensor technologies for weed detection
Site‐specific weed management is the part of precision agriculture (PA) that tries to
effectively control weed infestations with the least economical and environmental burdens …
effectively control weed infestations with the least economical and environmental burdens …