Dishwasher Tableware Recognition Based on Improved YOLOv8 Algorithm
This paper discusses the application of the improved YOLOv8 algorithm in the identification of stainless steel tableware.The YOLOv8 algorithm is an advanced deep learning model dedicated to real-time object recognition.The main innovations of this research focus on two aspects:First,Channel-Wise Mish module was introduced to improve the processing ability of nonlinear features in images.This improvement helps to classify and identify different tableware more accurately.Secondly,the optimized model effectively alleviates the common gradient disappearance problem in deep learning,thereby improving the training efficiency and detection accuracy.In this study,the ablation experiment was used to compare the performance of the model before and after the improvement,and to verify the effectiveness of the improved measures.In addition,compared with other common models such as FPN,YOLOX and Dynamic R-CNN,the improved algorithm performs better in terms of accuracy and generalization ability.
dishwasher tablewarevisual recognitionYOLOv8activation function
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