Gwo-Jiun Horng
Papers
4
Total Citations
166
H-Index
3
About
Dr. Gwo-Jiun Horng is a leading researcher at the intersection of artificial intelligence, computer vision, and smart agriculture. His work focuses on developing deep learning and IoT-based solutions to automate labor-intensive tasks in food production and robotics. Dr. Horng’s most impactful contribution is his 2019 study on a “Smart Image Recognition Mechanism for Crop Harvesting System in Intelligent Agriculture,” which has garnered 113 citations. This work pioneered the use of neural network object detection to determine crop maturity, enabling automated harvesting decisions that traditionally relied on extensive human experience. He further advanced agricultural automation with his 2019 paper on “Deep-Learning-Based Defective Bean Inspection with GAN-Structured Automated Labeled Data Augmentation in the Coffee Industry” (46 citations), which introduced a novel approach to automating the removal of defective coffee beans using generative adversarial networks. Dr. Horng has also contributed to robotics, proposing adaptive machine-learning systems for monocular vision-based object positioning and robotic arm guidance. His research is distinguished by its practical, industry-oriented applications, directly addressing real-world challenges in precision agriculture and manufacturing efficiency.
Research Focus
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Top Papers
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