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GANs and YOLOv11 for Automated Cochlear Hair Cell Detection
Book chapter

GANs and YOLOv11 for Automated Cochlear Hair Cell Detection

Cole Krudwig, Sara Avila, Ariana Mondiri, Adya Dhuler, Samantha Phillips, Ashlyn Viereck, Kaylee Van Handel and Steven Fernandes
Evolution in Computational Intelligence, pp.182-190
Smart Innovation, Systems and Technologies, Springer Nature Switzerland
07/02/2026

Abstract

Cochlear Hair Cell Detection GAN YOLOv11
Globally, more than 1.5 billion people are affected by hearing loss, which is approximately 20% of the global population. Children with hearing loss often do not receive the same level of education compared to their peers. With hair cell loss, sound is not converted as readily to neural activity in the cochlea. In this research, we have utilized the current state-of-the-art YOLOv11 method to detect cochlear hair cells and built a generative adversarial network (GAN) to generate synthetic images of cochlear hair cells. To the best of our knowledge, we are the first to use YOLOv11 for the detection of cochlear hair cells. The code for this project is available at https://github.com/Cole-Krudwig/GANs-YOLO-HC.

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