Survey: Gait Recognition Based on Image Energy

Ahmed, Dindar M.; Mahmood, Basil Sh.

doi:10.1109/icsgrc57744.2023.10215398

Cited by 3 publications

(1 citation statement)

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“…The intersection of deep learning and medical diagnostic technologies has become a focal point in academia [12], [15] other applications like face and gait recognition [16] and facial prediction [17]Significant strides have been made in this field. For example, in [18] Examines the fusion and influence of deep learning and artificial intelligence in the field of ophthalmology.…”

Section: B Current Research In DL For Oct-based Ophthalmic Disease Di...mentioning

confidence: 99%

OCT Images Diagnosis Based on Deep Learning – A Review

Abdi,

Abdulazeez

2024

ijcs

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The recent advancements in deep learning technology have significantly transformed the field of medical imaging, namely in the diagnosis of ocular illnesses. The progress made in this field has improved the capacity to extract and evaluate intricate characteristics in images, with Optical Coherence Tomography (OCT) playing a crucial role. OCT has become known for its safe qualities and its high level of detail, rendering it an essential instrument in the diagnosis of eye diseases. The interesting improvement in research is centered around the integration of deep learning with OCT for the purpose of automating the detection of eye diseases. We conducted a comprehensive study that explores several diagnostic methods and the wide-ranging uses of OCT. Additionally, it addresses the accessibility of publicly available datasets that are specifically tailored to optical coherence tomography (OCT). The paper provides a detailed review of the most recent advancements in computer-assisted diagnostic methods for diseases of the eye, such as age-related macular degeneration, glaucoma, and diabetic macular edema, with a particular focus on the effective use of OCT. Moreover, the paper systematically analyzes the primary challenges that deep learning faces in OCT image interpretation, emphasizing the intricate nature and possibilities of this field.

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