Surveying the Landscape: A Comprehensive Review of Object Detection Algorithms and Advancements

Hewa Majeed Zangana; Firas Mahmood Mustafa

doi:10.58602/jics.v3i1.29

Hewa Majeed Zangana IT Dept., Duhok Technical College, Duhok Polytechnic University, Duhok, Iraq
Firas Mahmood Mustafa Duhok Polytechnic University

DOI: https://doi.org/10.58602/jics.v3i1.29

Keywords: Computer Vision; Deep Learning; Image Processing; Object Detection

Abstract

This review paper gives a comprehensive investigation of the energetic scene of object detection, an essential field inside computer vision. Leveraging experiences from an assorted cluster of thinks about, the paper navigates through the chronicled advancement, techniques, challenges, later headways, applications, and future bearings in object detection.

The comparative examination dives into the complexities of conventional strategies versus profound learning approaches, the trade-offs between exactness and speed, and the vigor of models against ill-disposed assaults. Highlighting key measurements such as cross-modal location, ceaseless learning, and moral contemplations, the paper divulges the multifaceted nature of object detection techniques.

Applications of question discovery over spaces, counting independent vehicles, healthcare imaging, and keen cities, emphasize its transformative effect on different businesses. The talk amplifies to long term, envisioning challenges and openings in ranges such as ill-disposed vigor, cross-modal discovery, and moral contemplations.

As a comprehensive direct for analysts, professionals, and devotees, this paper not as it were capturing the current state of object detection but too serves as a compass for exploring the strange domains that lie ahead. The survey typifies the essence of protest detection's advancement and its significant suggestions, empowering proceeded investigation and advancement within the domain of computer vision.

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