Skripsi

DETEKSI OBJEK LIGHTWEIGHT LOW IMAGE MENGGUNAKAN ARSTITEKTUR YOLOv5.

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Penilaian

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Object detection is the process of identifying and localizing a specific object in an image or video that aims to recognize the presence and position of the object specifically. This technology has various applications in daily life, such as face detection to open smartphones. However, a major challenge in object detection is the camera's sensitivity to light intensity. In low lighting conditions, images may suffer from low contrast, resulting in blurry and distorted images. This condition can affect the performance of computer vision-based object detection systems. This research proposes the YOLOv5 model in low-light object detection systems. From the analysis, the YOLOv5x version of the model shows the best performance but has a larger size and complexity. Therefore, the YOLOv5m model with a confidence threshold of 0.3 is selected as a more efficient solution. This model offers a balance between precision, recall, and mAP, and has a moderate size compared to the other versions, making it suitable for object detection applications under various lighting conditions.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407006897	T161985	T1619852024	Central Library (REFERENCE)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1619852024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xii, 133 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.370 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Computer Vision
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

TUTI

Other version/related

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