Volume-12 , Issue-4 , Apr -2024, E-ISSN: 2347-2693

Objects are located by drawing a bounding box around the detected object. One of computer vision`s specialties is object detection, which finds things in an image or video. Techniques for object detection are the foundation of the area of artificial intelligence. Typically, object detection uses deep learning and machine learning to yield accurate and significant findings. It is essentially made up of localization and classification. The state-of-the-art techniques utilized for real-time object detection have advanced recently. This study paper compares state-of-the-art techniques, such as faster region convolutional neural networks (Faster R-CNN) and you only look once V8 (YOLOV8). These algorithms are deep neural network representations, or neural networks with numerous hidden layers. Although each of these algorithms is notable for its own distinctiveness, they are compared to see which is superior. This study focuses on determining which of these algorithms is more practical to employ despite sharing a common core, namely CNNs.

YOLOV8(You only look once), Faster region convolutional neural network (faster R-CNN), object detection, deep learning, deep neural networks, and convolutional neural networks.

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[3] A.M.A.ghani Abdulghani and G.G. Menekse Dalveren, “Moving Object Detection in Video with Algorithms YOLO and Faster R-CNN in Different Conditions,” European Journal of Science and Technology, Jan. 2022, DOI: 10.31590/ejosat.1013049.
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[6] JiayiFan; JangHyeon, Lee; InSuJung; YongKeunLee, “Improvement of Object Detection Based on Faster R-CNN and YOLO”, International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) June, pp.27-30 2021. DOI: 10.1109/ITC-CSCC52171.2021.9501480.
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DOI: 10.1109/ICCE-Asia49877.2020.9277040.
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DOI: 10.1109/IHMSC.2019.10157.
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B. Sai Jyothi, Chavali Saathvika Durga Abhinaya, Bellamkonda Lahari, Chinta Devika Priya, Devarapalli Anjali, Bathula Sri Navya, "Performance Evaluation on Real-time object detection using DL techniques," International Journal of Computer Sciences and Engineering, Vol.12, Issue.4, pp.75-80, 2024.

Optic Disc (OD) is the most critical component of the human retina where blood vessels originate. In the normal retinal image OD appears as a round, bright yellowish region. An efficient localization of OD in color retinal fundus images is the most vital phase for the retinal image analysis and this information helps in finding severity of retinal diseases. Identification of OD accurately is a very difficult and challenging task because of various reasons, including the presence of lesions around the OD and variation in size, shape and color of the optic disc. In this review paper, a brief introduction about OD and some important properties of it are described. A literature survey on OD detection and the complications involved in OD detection are also discussed in this paper.

Optic Disc (OD), Optic Nerve Head (ONH), Optic Cup (OC), Age Related Macular Degeneration (AMD), Diabetic Retinopathy (DR), Blood Vessels (BVs).

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Rajesh I.S., Bharathi Malakreddy A., Maithri C., Manjunath Sargur Krishnamurthy, Shashidhara M.S., "Automatic Detection of Optic Disc and Its Center in Color Retinal Images: A Review," International Journal of Computer Sciences and Engineering, Vol.12, Issue.4, pp.81-85, 2024.