التفاصيل البيبلوغرافية
| العنوان: |
The development and usability test of an automated fish counting system based on CNN and contrast limited histogram equalization. |
| المؤلفون: |
Jing Mei Leong, Ahmad Hijazi, Mohd Hanafi, Saudi, Azali, Chin Kim On, Ching Fui Fui, Haviluddin |
| المصدر: |
Bulletin of Electrical Engineering & Informatics; Apr2024, Vol. 13 Issue 2, p1128-1137, 10p |
| مصطلحات موضوعية: |
FISH population estimates, FISH populations, HATCHERY fishes, WEB-based user interfaces, FISH hatcheries |
| مستخلص: |
The aquaculture industry has rapidly grown over the year. One pertinent aspect is the ability of the aquaculture farm management to accurately count the fish populations to provide effective feeding and the control of breeding density. The current practice of counting the fish manually increased the hatchery workers workload and led to inefficiency. The presented work proposed an intelligent, web-based fish counting system to assist hatchery workers in counting fish from images. The methodology consists of two phases. First, an intelligent fish counting engine is developed. The captured image was first enhanced using the contrast limited adaptive histogram equalization. A deep learning architecture in the form of you only look once (YOLO)v5 is used to generate a model to identify and count fish on the image. Second, a web-based application is developed to implement the developed fish counting engine. When applied to the test data, the developed engine recorded a precision of 98.7% and a recall of 65.5%. The system is also evaluated by hatchery workers in the University Malaysia Sabah fish hatchery. The results of the usability and functionality evaluations indicate that the system is acceptable, with some future work suggested based on the feedback received. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
