MT-EfficientNetV2: A Multi-Temporal Scale Fusion EEG Emotion Recognition Method Based on Recurrence Plots by Zihan Zhang, Zhiyong Zhou, Jun Wang, Hao Hu, Jing Zhao

“…The model architecture incorporates DEconv and the SimAM attention mechanism with EfficientNetV2. This integration enhances the global fusion and expression of multi-scale features while strengthening the extraction of key emotional features at the local level, thereby suppressing redundant information. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

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Automated detection of diabetic retinopathy lesions in ultra-widefield fundus images using an attention-augmented YOLOv8 framework by Lei-Si Hu, Jie Wang, Heng-Ming Zhang, Hai-Yu Huang

“…ObjectiveTo enhance the automatic detection precision of diabetic retinopathy (DR) lesions, this study introduces an improved YOLOv8 model specifically designed for the precise identification of DR lesions.MethodThis study integrated two attention mechanisms, convolutional exponential moving average (convEMA) and convolutional simple attention module (convSimAM), into the backbone of the YOLOv8 model. …”
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Detection of Critical Parts of River Crab Based on Lightweight YOLOv7-SPSD by Guoai Fang, Yu Zhao

“…To enhance the lightweight nature of the YOLOv7-tiny model, we incorporate the Slimneck module, PConv, and the SimAM attention mechanism. …”
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