Image Processing Model for Classification of Stages of Freshness of Bangus using YOLOv8 Algorithm

Crowd recognition based on the fusion of multi-model collaboration

“…where here S o is the score of the object that is the output of object detection method [13].In this equation, S f is the score of the face that is the output of face detection method [14]. w f and w o are the weights that are computed based on the accuracy of models on the validation sets.S a is the revised score of the sample, where we can use a thresh value to filter the anomaly sample.…”

“…Object detection and face detection in the field of computer vision have always been widely studied hotspots, and many advanced models and methods have emerged, which contribute important ideas and technologies to the development of these two fields. With the rapid development of deep learning technology, advanced models such as YOLOv8 (You Only Look Once) [13] and SCNet (Spatial and Channel wise Attention in Convolutional Networks) [14] have emerged in object detection and face detection tasks. With their efficient and accurate characteristics, these models have led the research trend in related fields.…”

“…YOLOv8 [13] is a milestone work in the field of object detection and one of the latest versions of the YOLO series. Unlike the existing object detection methods, YOLOv8 adopts an end-to-end deep learning architecture to achieve one-time detection of all targets in the image.…”

Research on Rapid Recognition of Moving Small Targets by Robotic Arms Based on Attention Mechanisms

“…Figure 1 presents the main structure of YOLOv8. The detection effect of YOLOv8 demonstrates significant improvement compared to other mainstream object detection models [17]. By improving the accuracy of the detection algorithm, YOLOv8 enables more accurate target identification.…”