Kaplan-Kaplan Deep Learning for Computer Vision-Best Researcher Award

Kocaeli University-Turkey

Author Profile

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Early Academic Pursuits

Kaplan Kaplan's academic journey commenced at Kocaeli University, Turkey, where they pursued a Bachelor's in Mechatronic Engineering from 2007 to 2012. This foundation was followed by a Master's degree in Mechatronic Engineering from 2013 to 2015 and culminated in a Ph.D. in Mechatronic Engineering from Kocaeli University's Institute of Science and Technology in 2020.

Professional Endeavors

Transitioning into academia, Kaplan Kaplan undertook various roles at Kocaeli University, currently serving as an Assistant Professor in Software Engineering at the Faculty of Engineering since 2021. This role emphasizes their commitment to interdisciplinary engineering fields.

Contributions and Research Focus

With a research focus spanning algorithms, Artificial Intelligence, Computer Learning and Pattern Recognition, Software, and Biomedical Image Processing, Kaplan Kaplan's contributions are extensive and impactful. They've made significant strides in diverse areas, including:

• Fault Diagnosis: Specializing in fault diagnosis, particularly in bearing faults, Kaplan Kaplan has developed novel approaches using deep learning models and pattern recognition methods to diagnose faults accurately.
• Healthcare Applications: Their work in biomedical image processing extends to healthcare, contributing to brain tumor classification, thyroid nodule diagnosis, and spondyloarthritis detection through innovative machine learning algorithms applied to medical imaging.
• Machine Learning and AI: They've also delved into the development and optimization of machine learning algorithms, exploring their applications in various domains, including sustainable balanced scorecards, control systems, and predictive models for different scenarios.

Accolades and Recognition

Kaplan Kaplan's extensive publication record and contributions to academic literature are reflected in a substantial number of peer-reviewed articles, book chapters, and proceedings across prestigious international conferences. Their metrics, with 74 publications and notable citation indices (159 in WoS and 420 in Scopus), underscore their impact and influence in the academic domain.

Impact and Influence

Their multidisciplinary approach to engineering and AI has contributed significantly to advancing fault diagnosis methodologies, medical imaging applications, and the optimization of machine learning algorithms. These contributions have the potential to influence various industries, particularly in fault diagnosis systems, healthcare, and predictive analytics.

Legacy and Future Contributions

Kaplan Kaplan's legacy lies in their pioneering research that merges engineering principles with cutting-edge AI methodologies. Their future contributions are likely to continue shaping fault diagnosis systems, medical imaging technologies, and the broader landscape of machine learning applications in diverse industries, leaving a lasting impact on academia and practical implementations.

Notable Publications

• An emotion recognition method based on EWT-3D–CNN–BiLSTM-GRU-AT model
• of the brain metastases based on a new 3D deep learning architecture
• DEVELOPING A DEEP LEARNING MODEL ON CONVENTIONAL X-RAYS IN THE DIAGNOSIS OF AXIAL SPONDYLOARTHRITIS
• Şeker hastalığı teşhisi ve önerilen modellerinin karşılaştırılması
• Human Face Recognition Using Deep Neural Networks