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Synchronizing Object Detection: Applications, Advancements and Existing Challenges

2024; Institute of Electrical and Electronics Engineers; Volume: 12; Linguagem: Inglês

10.1109/access.2024.3388889

2169-3536

Md. Tanzib Hosain, Asif Zaman, Mushfiqur Rahman Abir, Shanjida Akter, Sawon Mursalin, Shadman Sakeeb Khan,

Advanced Image and Video Retrieval Techniques

From pivotal roles in autonomous vehicles, healthcare diagnostics, and surveillance systems to seamlessly integrating with augmented reality, object detection algorithms stand as the cornerstone in unraveling the complexities of the visual world. Tracing the trajectory from conventional region-based methods to the latest neural network architectures reveals a technological renaissance where algorithms metamorphose into digital artisans. However, this journey is not without hurdles, prompting researchers to grapple with real-time detection, robustness in varied environments, and interpretability amidst the intricacies of deep learning. The allure of addressing issues such as occlusions, scale variations, and fine-grained categorization propels exploration into uncharted territories, beckoning the scholarly community to contribute to an ongoing saga of innovation and discovery. This research offers a comprehensive panorama, encapsulating the applications reshaping our digital reality, the advancements pushing the boundaries of perception, and the open issues extending an invitation to the next generation of visionaries to explore uncharted frontiers within object detection.