Paper Title
STUDY ON UNDERSTANDING COMPUTER VISION APPLICATIONS
Article Identifiers
Authors
Matrika Regmi
Keywords
Computer Vision, OpenCV, Tensorflow, Detection
Abstract
This paper examines the role of computer vision in enhancing machines’ interaction with visual data. Utilizing Python, the study presents applications such as face, motion, mask, and vehicle detection. The methodology involved data collection and model training using datasets like FDDB and KITTI. Results showed high accuracy rates: 95% for face detection, 99.2% for vehicle detection, and 90% for mask detection. The paper suggests future research to improve model robustness and explore new sensor technologies, underscoring computer vision’s growing impact on daily life.
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How To Cite (APA)
Matrika Regmi (April-2024). STUDY ON UNDERSTANDING COMPUTER VISION APPLICATIONS. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), j15-j28. https://ijnrd.org/papers/IJNRD2404903.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : j15-j28
Other Publication Details
Paper Reg. ID: IJNRD_220348
Published Paper Id: IJNRD2404903
Downloads: 000121986
Research Area: Computer Science & TechnologyÂ
Country: Kathmandu, Bagmati, Nepal
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404903.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404903
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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