[HTML][HTML] Transforming weed management in sustainable agriculture with artificial intelligence: A systematic literature review towards weed identification and deep …

M Vasileiou, LS Kyrgiakos, C Kleisiari, G Kleftodimos… - Crop Protection, 2024 - Elsevier
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 …

[HTML][HTML] Performance evaluation of deep learning object detectors for weed detection for cotton

A Rahman, Y Lu, H Wang - Smart Agricultural Technology, 2023 - Elsevier
Alternative non-chemical or chemical-reduced weed control tactics are critical for future
integrated weed management, especially for herbicide-resistant weeds. Through weed …

[HTML][HTML] Effect of varying training epochs of a faster region-based convolutional neural network on the accuracy of an automatic weed classification scheme

OG Ajayi, J Ashi - Smart Agricultural Technology, 2023 - Elsevier
Site-specific weed detection and management is a crucial approach for crop production
management and herbicide contamination mitigation in precision agriculture. With the …

[HTML][HTML] A Review on the High-Efficiency Detection and Precision Positioning Technology Application of Agricultural Robots

R Wang, L Chen, Z Huang, W Zhang, S Wu - Processes, 2024 - mdpi.com
The advancement of agricultural technology has increasingly positioned robotic detection
and localization techniques at the forefront, ensuring critical support for agricultural …

[HTML][HTML] Deep learning-based object detection system for identifying weeds using uas imagery

A Etienne, A Ahmad, V Aggarwal, D Saraswat - Remote Sensing, 2021 - mdpi.com
Current methods of broadcast herbicide application cause a negative environmental and
economic impact. Computer vision methods, specifically those related to object detection …

[HTML][HTML] Object-level benchmark for deep learning-based detection and classification of weed species

ASMM Hasan, D Diepeveen, H Laga, MGK Jones… - Crop Protection, 2024 - Elsevier
Weeds can decrease yields and the quality of crops. Detection, localisation, and
classification of weeds in crops are crucial for developing efficient weed control and …

[HTML][HTML] Comparative performance of YOLOv8, YOLOv9, YOLOv10, YOLOv11 and Faster R-CNN models for detection of multiple weed species

A Sharma, V Kumar, L Longchamps - Smart Agricultural Technology, 2024 - Elsevier
Weeds pose a serious production challenge in various agronomic crops by reducing their
grain yields. Increasing cases of herbicide-resistant (HR) weed populations further …

TobSet: A new tobacco crop and weeds image dataset and its utilization for vision-based spraying by agricultural robots

MS Alam, M Alam, M Tufail, MU Khan, A Güneş… - Applied Sciences, 2022 - mdpi.com
Selective agrochemical spraying is a highly intricate task in precision agriculture. It requires
spraying equipment to distinguish between crop (plants) and weeds and perform spray …

Use of open-source object detection algorithms to detect Palmer amaranth (Amaranthus palmeri) in soybean

IH Barnhart, S Lancaster, D Goodin, J Spotanski… - Weed Science, 2022 - cambridge.org
Site-specific weed management using open-source object detection algorithms could
accurately detect weeds in cropping systems. We investigated the use of object detection …

Feasibility study of fish disease detection using computer vision and deep convolutional neural network (dcnn) algorithm

ML Yasruddin, MAH Ismail, Z Husin… - 2022 IEEE 18th …, 2022 - ieeexplore.ieee.org
Detection of diseased fish at an early stage is necessary to prevent the spread of the
disease. However, detecting fish diseases still uses a manual process and requires a high …