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This repository is a literature review on object detection advancements, focusing on YOLOv8. It explores the evolution from basic techniques to CNN and YOLO, highlighting YOLOv8's efficiency, accuracy, and speed in real-time applications.

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Object Detection: Innovations and Real-World Applications

About This Repository

This repository contains a comprehensive literature review on the advancements in object detection technology, with a focus on the development and applications of YOLOv8. The review covers the evolution of object detection from early techniques to advanced methods like CNN and YOLO architectures.

Key Sections

  • Introduction to Object Detection Technology
  • Evolution of Object Detection Techniques
  • Overview of the YOLO Architecture and YOLOv8
  • Comparative Analysis of Object Detection Models
  • Challenges and Limitations in Current Research
  • Future Directions in Object Detection

Highlights

  • In-depth exploration of YOLOv8's algorithmic improvements, accuracy enhancements, and practical implications.
  • Comparative analysis of YOLOv8 with other object detection models.
  • Discussion on the ethical and privacy concerns in object detection technology.
  • Examination of future research directions, including specialized hardware development and ethical considerations.

About

This repository is a literature review on object detection advancements, focusing on YOLOv8. It explores the evolution from basic techniques to CNN and YOLO, highlighting YOLOv8's efficiency, accuracy, and speed in real-time applications.

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