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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

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 infestations can cause extensive damage to wheat and sorghum fields and spread plant viruses, resulting in significant yield losses in agriculture. To address this issue, farmers often rely on chemical pesticides, which are…

Computer Vision and Pattern Recognition · Computer Science 2023-07-21 Raiyan Rahman , Christopher Indris , Tianxiao Zhang , Kaidong Li , 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

The development of practical and robust automated diagnostic systems for identifying plant pests is crucial for efficient agricultural production. In this paper, we first investigate three key research questions (RQs) that have not been…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Ryosuke Wayama , Yuki Sasaki , Satoshi Kagiwada , Nobusuke Iwasaki , Hitoshi Iyatomi

Insect pests continue to bring a serious threat to crop yields around the world, and traditional methods for monitoring them are often slow, manual, and difficult to scale. In recent years, deep learning has emerged as a powerful solution,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Muhammad Hassam Ejaz , Muhammad Bilal , Usman Habib , Muhammad Attique , Tae-Sun Chung

The protection of crops from pests is relevant for any cultivated crop. But modern methods of pest control by pesticides carry many dangers for humans. Therefore, research into the development of safe and effective pest control methods is…

Computer Vision and Pattern Recognition · Computer Science 2021-05-10 Rakhmatulin Ildar

One of the critical biotic stress factors paddy farmers face is diseases caused by bacteria, fungi, and other organisms. These diseases affect plants' health severely and lead to significant crop loss. Most of these diseases can be…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Petchiammal A , Briskline Kiruba S , D. Murugan , Pandarasamy A

Monitoring the number of insect pests is a crucial component in pheromone-based pest management systems. In this paper, we propose an automatic detection pipeline based on deep learning for identifying and counting pests in images taken…

Computer Vision and Pattern Recognition · Computer Science 2016-02-25 Weiguang Ding , Graham Taylor

Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and…

Computer Vision and Pattern Recognition · Computer Science 2016-04-18 Sharada Prasanna Mohanty , David Hughes , Marcel Salathe

Accurate identification of agricultural pests is essential for crop protection but remains challenging due to the large intra-class variance and fine-grained differences among pest species. While deep learning has advanced pest detection,…

Artificial Intelligence · Computer Science 2025-05-06 Jiaqi Zhang , Zhuodong Liu , Kejian Yu

Every year, plant parasitic nematodes, one of the major groups of plant pathogens, cause a significant loss of crops worldwide. To mitigate crop yield losses caused by nematodes, an efficient nematode monitoring method is essential for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Zhipeng Yuan , Nasamu Musa , Katarzyna Dybal , Matthew Back , Daniel Leybourne , Po Yang

In precision agriculture, the detection and recognition of insects play an essential role in the ability of crops to grow healthy and produce a high-quality yield. The current machine vision model requires a large volume of data to achieve…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Hoang-Quan Nguyen , Thanh-Dat Truong , Xuan Bac Nguyen , Ashley Dowling , Xin Li , Khoa Luu

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

Accurate insect pest recognition is significant to protect the crop or take the early treatment on the infected yield, and it helps reduce the loss for the agriculture economy. Design an automatic pest recognition system is necessary…

Computer Vision and Pattern Recognition · Computer Science 2021-07-27 Hieu T. Ung , Huy Q. Ung , Binh T. Nguyen

Weeds are a major threat to crops and are responsible for reducing crop yield worldwide. To mitigate their negative effect, it is advantageous to accurately identify them early in the season to prevent their spread throughout the field.…

Computer Vision and Pattern Recognition · Computer Science 2022-04-04 Varun Aggarwal , Aanis Ahmad , Aaron Etienne , Dharmendra Saraswat

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

Panicle density of cereal crops such as wheat and sorghum is one of the main components for plant breeders and agronomists in understanding the yield of their crops. To phenotype the panicle density effectively, researchers agree there is a…

Computer Vision and Pattern Recognition · Computer Science 2020-04-20 Akshay L Chandra , Sai Vikas Desai , Vineeth N Balasubramanian , Seishi Ninomiya , Wei Guo

Insects represent half of all global biodiversity, yet many of the world's insects are disappearing, with severe implications for ecosystems and agriculture. Despite this crisis, data on insect diversity and abundance remain woefully…

Biodiversity monitoring is crucial for tracking and counteracting adverse trends in population fluctuations. However, automatic recognition systems are rarely applied so far, and experts evaluate the generated data masses manually.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-31 Dimitri Korsch , Paul Bodesheim , Joachim Denzler
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