Intelligence technologies play an important role in increasing product quality and production
efficiency in digital aquaculture. Automatic fish detection will contribute to achieving …

Fish classification (FC) is an expansively studied problem in the domains of image
segmentation, pattern recognition, and information retrieval. It has been applied in a …

Due to the recent technology development, the multimedia complexity is noticeably
increased and new research areas are opened relying on similar multimedia content …

Content based image retrieval (CBIR) systems work by retrieving images which are related
to the query image (QI) from huge databases. The available CBIR systems extract limited …

Detection of pests in the paddy fields is a major challenge in the field of agriculture, therefore
effective measures should be developed to fight the infestation while minimizing the use of …

Content based image retrieval (CBIR) systems retrieve images linked to the query image
(QI) from enormous databases. The feature sets extracted by the present CBIR systems are …

Fish image segmentation can be considered an essential process in developing a system
for fish recognition. This task is challenging as different specimens, rotations, positions …

Fish recognition is presently a very complex and difficult task despite its commercial and
agricultural usefulness. Some of the challenges facing accurate and reliable fish recognition …

This paper discusses research in the area of texture image classification. More specifically,
the combination of texture and colour features is researched. The principle objective is to …

Image recognition process could be plagued by many problems including noise, overlap,
distortion, errors in the outcomes of segmentation, and impediment of objects within the …