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Related papers: On the Real-Time Semantic Segmentation of Aphid Cl…

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Aphid infestations are one of the primary causes of extensive damage to wheat and sorghum fields and are one of the most common vectors for plant viruses, resulting in significant agricultural yield losses. To address this problem, farmers…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Raiyan Rahman , Christopher Indris , Goetz Bramesfeld , Tianxiao Zhang , Kaidong Li , Xiangyu Chen , Ivan Grijalva , Brian McCornack , Daniel Flippo , Ajay Sharda , Guanghui Wang

Aphid infestation poses a significant threat to crop production, rural communities, and global food security. While chemical pest control is crucial for maximizing yields, applying chemicals across entire fields is both environmentally…

Computer Vision and Pattern Recognition · Computer Science 2023-08-14 Tianxiao Zhang , Kaidong Li , Xiangyu Chen , Cuncong Zhong , Bo Luo , Ivan Grijalva , Brian McCornack , Daniel Flippo , Ajay Sharda , Guanghui Wang

Aphids are one of the main threats to crops, rural families, and global food security. Chemical pest control is a necessary component of crop production for maximizing yields, however, it is unnecessary to apply the chemical approaches to…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Tianxiao Zhang , Kaidong Li , Xiangyu Chen , Cuncong Zhong , Bo Luo , Ivan Grijalva Teran , Brian McCornack , Daniel Flippo , Ajay Sharda , Guanghui Wang

Aphids can cause direct damage and indirect virus transmission to crops. Timely monitoring and control of their populations are thus critical. However, the manual counting of aphids, which is the most common practice, is labor-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Xumin Gao , Wenxin Xue , Callum Lennox , Mark Stevens , Junfeng Gao

Real-time semantic segmentation of remote sensing imagery is a challenging task that requires a trade-off between effectiveness and efficiency. It has many applications including tracking forest fires, detecting changes in land use and land…

Computer Vision and Pattern Recognition · Computer Science 2023-09-13 Clifford Broni-Bediako , Junshi Xia , Naoto Yokoya

In weed control, precision agriculture can help to greatly reduce the use of herbicides, resulting in both economical and ecological benefits. A key element is the ability to locate and segment all the plants from image data. Modern…

Computer Vision and Pattern Recognition · Computer Science 2023-03-16 Patrick Zimmer , Michael Halstead , Chris McCool

Selective weeding is one of the key challenges in the field of agriculture robotics. To accomplish this task, a farm robot should be able to accurately detect plants and to distinguish them between crop and weeds. Most of the promising…

Computer Vision and Pattern Recognition · Computer Science 2017-12-19 Maurilio Di Cicco , Ciro Potena , Giorgio Grisetti , Alberto Pretto

Semantic segmentation is the problem of assigning a class label to every pixel in an image, and is an important component of an autonomous vehicle vision stack for facilitating scene understanding and object detection. However, many of the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Christopher J. Holder , Muhammad Shafique

Accurate segmentation of foliar diseases and insect damage in wheat is crucial for effective crop management and disease control. However, the insect damage typically occupies only a tiny fraction of annotated pixels. This extreme…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Tianqi Wei , Xin Yu , Zhi Chen , Scott Chapman , Zi Huang

Semantic segmentation is a fundamental task for agricultural robots to understand the surrounding environments in natural orchards. The recent development of the LiDAR techniques enables the robot to acquire accurate range measurements of…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Hanwen Kang , Xing Wang

Agricultural losses to pest represent an important challenge in a global warming scenario. Intercropping is an alternative farming practice that promotes pest control without the use of chemical pesticides. Here we develop a mathematical…

Populations and Evolution · Quantitative Biology 2019-09-11 Alfonso Allen-Perkins , Ernesto Estrada

This paper introduces a methodology for generating synthetic annotated data to address data scarcity in semantic segmentation tasks within the precision agriculture domain. Utilizing Denoising Diffusion Probabilistic Models (DDPMs) and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Andrew Heschl , Mauricio Murillo , Keyhan Najafian , Farhad Maleki

Plant diseases are major causes of production losses and may have a significant impact on the agricultural sector. Detecting pests as early as possible can help increase crop yields and production efficiency. Several robotic monitoring…

Robotics · Computer Science 2023-08-29 Adi Yehoshua , Yael Edan

The existence of real-world adversarial examples (commonly in the form of patches) poses a serious threat for the use of deep learning models in safety-critical computer vision tasks such as visual perception in autonomous driving. This…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Giulio Rossolini , Federico Nesti , Gianluca D'Amico , Saasha Nair , Alessandro Biondi , Giorgio Buttazzo

Precision farming robots, which target to reduce the amount of herbicides that need to be brought out in the fields, must have the ability to identify crops and weeds in real time to trigger weeding actions. In this paper, we address the…

Computer Vision and Pattern Recognition · Computer Science 2018-03-05 Andres Milioto , Philipp Lottes , Cyrill Stachniss

Weed scouting is an important part of modern integrated weed management but can be time consuming and sparse when performed manually. Automated weed scouting and weed destruction has typically been performed using classification systems…

Computer Vision and Pattern Recognition · Computer Science 2017-02-28 David Hall , Feras Dayoub , Jason Kulk , Chris McCool

Effective pest management is crucial for enhancing agricultural productivity, especially for crops such as sugarcane and wheat that are highly vulnerable to pest infestations. Traditional pest management methods depend heavily on manual…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Anirudha Ghosh , Ritam Sarkar , Debaditya Barman

Uncontrolled growth of weeds can severely affect the crop yield and quality. Unrestricted use of herbicide for weed removal alters biodiversity and cause environmental pollution. Instead, identifying weed-infested regions can aid selective…

Computer Vision and Pattern Recognition · Computer Science 2021-02-22 Shantam Shorewala , Armaan Ashfaque , Sidharth R , Ujjwal Verma

One of the biggest challenges that the farmers go through is to fight insect pests during agricultural product yields. The problem can be solved easily and avoid economic losses by taking timely preventive measures. This requires…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Mohtasim Hadi Rafi , Mohammad Ratul Mahjabin , Md Sabbir Rahman

Semantic segmentation works on the computer vision algorithm for assigning each pixel of an image into a class. The task of semantic segmentation should be performed with both accuracy and efficiency. Most of the existing deep FCNs yield to…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Farshad Safavi , Irfan Ali , Venkatesh Dasari , Guanqun Song , Ting Zhu , Maryam Rahnemoonfar
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