1. IBON: Image based ornithological identification mobile application - A mobile application development for image based classification of birds in Tablas.
- Author
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Tupas, Preexcy B., Lucidos, Juniel G., Forcado, Marvin Rick G., Aguila, Catherine Bhel B., Aguila, John Joseph G., and Fradejas, Dayne N.
- Subjects
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MACHINE learning , *COMPUTER vision , *BIRD classification , *MOBILE apps , *USER interfaces - Abstract
The study introduces "IBON," a pioneering mobile application tailored for ornithologists, bird enthusiasts, and nature researchers seeking to streamline the identification and classification of avian species in Tablas, a region known for its ecological diversity. In response to the growing demand for user-friendly, technology-driven solutions for bird species documentation, IBON presents an innovative approach, harnessing the potential of real-time image recognition. IBON is a mobile application that employs advanced deep learning algorithms and computer vision techniques to recognize and classify bird species in real-time, based on images captured directly through the device's camera. This paper explores the development process, the distinctive features, and the technical intricacies of IBON, including its real-time image recognition model and user interface. The validation of IBON predominantly centers on training and testing accuracy, involving rigorous assessments to ensure the reliability of species identification. The paper details the methodology and results of these accuracy tests, shedding light on the application's performance metrics. It represents a significant contribution to ornithological research and mobile application development for ecological monitoring and conservation, as it allows for instantaneous bird identification through the device's camera while maintaining high levels of accuracy. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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