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Mosquito-related diseases pose a significant threat to global public health, necessitating efficient and accurate mosquito classification for effective surveillance and control. This work presents an innovative approach to mosquito…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Ahmed Akib Jawad Karim , Muhammad Zawad Mahmud , Riasat Khan

Pollinator insects such as honeybees and bumblebees are vital to global food production and ecosystem stability, yet their populations are declining due to anthropogenic and environmental stressors. Scalable, automated monitoring in…

Computer Vision and Pattern Recognition · Computer Science 2025-09-10 Ahmed Emam , Mohamed Elbassiouny , Julius Miller , Patrick Donworth , Sabine Seidel , Ribana Roscher

Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and…

Fruit harvesting poses a significant labor and financial burden for the industry, highlighting the critical need for advancements in robotic harvesting solutions. Machine vision-based fruit detection has been recognized as a crucial…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Jiajia Li , Kyle Lammers , Xunyuan Yin , Xiang Yin , Long He , Renfu Lu , Zhaojian Li

Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging and so forth. A good number of motion detectors have been identified in the insects' visual pathways.…

Computer Vision and Pattern Recognition · Computer Science 2019-04-04 Qinbing Fu , Hongxin Wang , Cheng Hu , Shigang Yue

Insect pests recognition is necessary for crop protection in many areas of the world. In this paper we propose an automatic classifier based on the fusion between saliency methods and convolutional neural networks. Saliency methods are…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Loris Nanni , Gianluca Maguolo , Fabio Pancino

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

Pest and disease classification is a challenging issue in agriculture. The performance of deep learning models is intricately linked to training data diversity and quantity, posing issues for plant pest and disease datasets that remain…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Zhengle Wang , Ruifeng Wang , Minjuan Wang , Tianyun Lai , Man Zhang

Nematode worms are one of most abundant metazoan groups on the earth, occupying diverse ecological niches. Accurate recognition or identification of nematodes are of great importance for pest control, soil ecology, bio-geography, habitat…

Quantitative Methods · Quantitative Biology 2021-03-16 Xuequan Lu , Yihao Wang , Sheldon Fung , Xue Qing

We present IMDD-1M, the first large-scale Industrial Multimodal Defect Dataset comprising 1,000,000 aligned image-text pairs, designed to advance multimodal learning for manufacturing and quality inspection. IMDD-1M contains high-resolution…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 TsaiChing Ni , ZhenQi Chen , YuanFu Yang

Among all animals, mosquitoes are responsible for the most deaths worldwide. Interestingly, not all types of mosquitoes spread diseases, but rather, a select few alone are competent enough to do so. In the case of any disease outbreak, an…

Computer Vision and Pattern Recognition · Computer Science 2020-07-23 Mona Minakshi , Pratool Bharti , Willie B. McClinton , Jamshidbek Mirzakhalov , Ryan M. Carney , Sriram Chellappan

Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity. This paper presents a system for liberating useful information from physical collections by bringing specimens into…

Computer Vision and Pattern Recognition · Computer Science 2017-09-08 Chuong V. Nguyen , David R. Lovell , Matt Adcock , John La Salle

Accurate pest population monitoring and tracking their dynamic changes are crucial for precision agriculture decision-making. A common limitation in existing vision-based automatic pest counting research is that models are typically…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Xumin Gao , Mark Stevens , Grzegorz Cielniak

With the rapid development of deep learning, many deep learning-based approaches have made great achievements in object detection task. It is generally known that deep learning is a data-driven method. Data directly impact the performance…

Computer Vision and Pattern Recognition · Computer Science 2021-03-26 Xian Sun , Peijin Wang , Zhiyuan Yan , Feng Xu , Ruiping Wang , Wenhui Diao , Jin Chen , Jihao Li , Yingchao Feng , Tao Xu , Martin Weinmann , Stefan Hinz , Cheng Wang , Kun Fu

Accurate insect pest recognition plays a critical role in agriculture. It is a challenging problem due to the intricate characteristics of insects. In this paper, we present DeWi, novel learning assistance for insect pest classification.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Toan Nguyen , Huy Nguyen , Huy Ung , Hieu Ung , Binh Nguyen

Insect production for food and feed presents a promising supplement to ensure food safety and address the adverse impacts of agriculture on climate and environment in the future. However, optimisation is required for insect production to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Min Ren , Yunlong Wang , Yuhao Zhu , Yongzhen Huang , Zhenan Sun , Qi Li , Tieniu Tan

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

DepthCropSeg++: a foundation model for crop segmentation, capable of segmenting different crop species under open in-field environment. Crop segmentation is a fundamental task for modern agriculture, which closely relates to many downstream…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Jiafei Zhang , Songliang Cao , Binghui Xu , Yanan Li , Weiwei Jia , Tingting Wu , Hao Lu , Weijuan Hu , Zhiguo Han

Nowadays, due to the rapid population expansion, food shortage has become a critical issue. In order to stabilizing the food source production, preventing crops from being attacked by pests is very important. In generally, farmers use…

Computer Vision and Pattern Recognition · Computer Science 2021-07-16 Shi-Yao Zhou , Chung-Yen Su

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