Bridging Vision and Industry: Real-World Applications of Image Segmentation and Edge Detection, KPR Institute Engineering and Technology, Autonomous Engineering Institution, Coimbatore, India

Title
Bridging Vision and Industry: Real-World Applications of Image Segmentation and Edge Detection

Hybrid Event
Bridging Vision and Industry: Real-World Applications of Image Segmentation and Edge Detection
Expert Talk Dept. Level
DATE
Oct 29, 2025 to Oct 31, 2025
TIME
06:00 PM to 10:00 PM
DEPARTMENT
AM
TOTAL PARTICIPATES
11
Bridging Vision and Industry: Real-World Applications of Image Segmentation and Edge Detection
Summary

The event “Bridging Vision and Industry: Real-World Applications of Image Segmentation and Edge Detection” successfully provided participants with practical insights into how computer vision technologies are applied across various industries. Students gained a strong conceptual understanding of image segmentation techniques, edge detection algorithms, and their significance in enabling machines to interpret visual data accurately.

The resource person demonstrated real-world industrial applications, including medical image diagnosis, automated manufacturing inspection, autonomous navigation systems, surveillance and security analytics, and multimedia processing. These demonstrations helped students clearly understand how theoretical image-processing concepts translate into high-impact industry solutions.

Participants actively engaged in discussions, clarified technical queries, and showed enthusiasm in exploring hands-on applications of the concepts presented. The session effectively enhanced students’ awareness of current trends, tools, and technologies used in computer vision, motivating them to take up related academic projects, research topics, and career opportunities in AI and image processing.

Overall, the event achieved its intended outcomes by strengthening participants’ technical competency, improving their practical understanding of computer vision workflows, and bridging the gap between academic learning and real-world industry applications.


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