科研产出
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1A Deep Learning-Based Object Detection Scheme by Improving YOLOv5 for Sprouted Potatoes Datasets
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来源：IEEE ACCESS
关键词： Object detection; convolutional neural network; sprouting potato recognition; mosaic; hyperparametric optimization; spatial pyramid pooling
年份：2022
2An Industrial-Grade Solution for Crop Disease Image Detection Tasks
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机构：
来源：FRONTIERS IN PLANT SCIENCE
关键词： crop disease detection; convolutional neural network; model compression; knowledge distillation; activate quantitative; model deployment
年份：2022
3DA-ActNN-YOLOV5: Hybrid YOLO v5 Model with Data Augmentation and Activation of Compression Mechanism for Potato Disease Identification
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机构：
来源：COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
年份：2022
4DFN-PSAN: Multi-level deep information feature fusion extraction network for interpretable plant disease classification
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机构：
来源：COMPUTERS AND ELECTRONICS IN AGRICULTURE
关键词： Deep learning; Image processing; Feature fusion; Multilevel features; Pixel attention; Disease classification
年份：2024
5PPLC-Net:Neural network-based plant disease identification model supported by weather data augmentation and multi-level attention mechanism
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机构：
来源：JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
关键词： Convolutional neural network; Dilated convolutions; Global average pooling; Attention mechanism (CBAM); Weather data augmentation; Leaf disease recognition
年份：2023
6ITF-WPI: Image and text based cross-modal feature fusion model for wolfberry pest recognition
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机构：
来源：COMPUTERS AND ELECTRONICS IN AGRICULTURE
关键词： Cross-modal fusion; Contextual transformer; Pyramid squeeze attention mechanism; Convolutional neural network and bi-; directional long short-term memory; Pest recognition
年份：2023
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