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Related papers: Computer Vision Approaches for Automated Bee Count…

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Wide use and availability of the machine learning and computer vision techniques allows development of relatively complex monitoring systems in many domains. Besides the traditional industrial domain, new application appears also in biology…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Simon Bilik , Tomas Zemcik , Lukas Kratochvila , Dominik Ricanek , Milos Richter , Sebastian Zambanini , Karel Horak

The purpose of the Insect Detection System for Crop and Plant Health is to keep an eye out for and identify insect infestations in farming areas. By utilizing cutting-edge technology like computer vision and machine learning, the system…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Md. Mahmudul Hasan , SM Shaqib , Ms. Sharmin Akter , Rabiul Alam , Afraz Ul Haque , Shahrun akter khushbu

Accurately counting maize tassels is important for monitoring the growth status of maize plants. This tedious task, however, is still mainly done by manual efforts. In the context of modern plant phenotyping, automating this task is…

Computer Vision and Pattern Recognition · Computer Science 2017-07-11 Hao Lu , Zhiguo Cao , Yang Xiao , Bohan Zhuang , Chunhua Shen

Honey bees pollinate about one-third of the world's food supply, but bee colonies have alarmingly declined by nearly 40% over the past decade due to several factors, including pesticides and pests. Traditional methods for monitoring…

Machine Learning · Computer Science 2024-01-19 Andrew Liang

Honey bees play a crucial role in pollination, contributing significantly to global agriculture and ecosystems. Accurately estimating hive populations is essential for understanding the effects of environmental factors on bee colonies, yet…

Quantitative Methods · Quantitative Biology 2025-12-15 Junmin Zhong , Jon F. Harrison , Jennie Si , Jun Chen

In this paper, we show that paint markings are a feasible approach to automatize the analysis of behavioral assays involving honey bees in the field where marking has to be as lightweight as possible. We contribute a novel dataset for bees…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Luke Meyers , Josué Rodríguez Cordero , Carlos Corrada Bravo , Fanfan Noel , José Agosto-Rivera , Tugrul Giray , Rémi Mégret

In this paper we propose a network aware approach for routing in graded network using Artificial Bee Colony (ABC) algorithm. ABC has been used as a good search process for optimality exploitation and exploration. The paper shows how ABC…

Networking and Internet Architecture · Computer Science 2014-08-06 Kavitha Sooda , T. R. Gopalakrishnan Nair

With fine-grained classification, we identify unique characteristics to distinguish among classes of the same super-class. We are focusing on species recognition in Insecta, as they are critical for biodiversity monitoring and at the base…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Rita Pucci , Vincent J. Kalkman , Dan Stowell

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

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

Automatic bacterial colony counting is a highly sought-after technology in modern biological laboratories because it eliminates manual counting effort. Previous work has observed that MicrobiaNet, currently the best-performing cardinality…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Minghua Zheng , Na Helian , Peter C. R. Lane , Yi Sun , Allen Donald

This study presents a novel method for improving rice disease classification using 8 different convolutional neural network (CNN) algorithms, which will further the field of precision agriculture. Tkinter-based application that offers…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Biplov Paneru , Bishwash Paneru , Krishna Bikram Shah

This paper explores the use of the Artificial Bee Colony (ABC) algorithm to compute threshold selection for image segmentation. ABC is a heuristic algorithm motivated by the intelligent behavior of honey-bees which has been successfully…

Computer Vision and Pattern Recognition · Computer Science 2014-05-29 Erik Cuevas , Felipe Sencion , Daniel Zaldivar , Marco Perez , Humberto Sossa

Preserving the number and diversity of insects is one of our society's most important goals in the area of environmental sustainability. A prerequisite for this is a systematic and up-scaled monitoring in order to detect correlations and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Danja Brandt , Martin Tschaikner , Teodor Chiaburu , Henning Schmidt , Ilona Schrimpf , Alexandra Stadel , Ingeborg E. Beckers , Frank Haußer

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

Automated recognition and classification of bacteria species from microscopic images have significant importance in clinical microbiology. Bacteria classification is usually carried out manually by biologists using different shapes and…

Quantitative Methods · Quantitative Biology 2019-12-19 Muhammed Talo

Agriculture is vital for human survival and remains a major driver of several economies around the world; more so in underdeveloped and developing economies. With increasing demand for food and cash crops, due to a growing global population…

Computer Vision and Pattern Recognition · Computer Science 2018-11-21 Daniel K. Nkemelu , Daniel Omeiza , Nancy Lubalo

Insects are the most important global pollinator of crops and play a key role in maintaining the sustainability of natural ecosystems. Insect pollination monitoring and management are therefore essential for improving crop production and…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Malika Nisal Ratnayake , Don Chathurika Amarathunga , Asaduz Zaman , Adrian G. Dyer , Alan Dorin

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…

Aedes aegypti is still one of the main concerns when it comes to disease vectors. Among the many ways to deal with it, there are important protocols that make use of egg numbers in ovitraps to calculate indices, such as the LIRAa and the…

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