The intelligent identification of tea diseases is crucial for ensuring tea quality and reducing economic losses in the tea industry. However, the deployment of deep learning models on edge devices remains challenging due to the conflict between detection accuracy and computational overhead. To address this, we propose CA-YOLOv8n, a lightweight object detection model tailored for tea disease diagnosis. Specifically, we introduce a Path-Decoupling strategy to streamline the network structure and integrate the Coordinate Attention (CA) mechanism to enhance the model's spatial awareness of subtle pathological features. Experimental results demonstrate that the proposed model achieves a mean Average Precision (mAP@50) of 98.89% while reducing the parameter count by 32.6% and FLOPs by 24.1% compared to the baseline YOLOv8n. The model was integrated into a diagnostic platform with an automated reporting interface, demonstrating that real-time tea disease identification is feasible on commodity CPU hardware in resource-constrained agricultural environments.
Multi-view subspace clustering has progressed significantly by using deep neural networks to handle nonlinear data representations. A recent advancement, the Multi-view Self-Expressive Subspace Clustering (MSESC) network, achieves markedly higher computational efficiency by subst…
Eruption of volcanoes is associated with the emission of great energy through the propagation of atmospheric waves up into space. These waves cause significant disturbances in the ionosphere, a region that contains a large number of ions and electrons and is important in providin…
Ninety percent of drugs fail during clinical trials, mainly due to lack of clinical efficacy. Recent developments in in vitro models such as 3D tumor heterospheroids have led to improvements in failure rates, but the relative lack of standardized evaluation methods for 3D culture…
Social media has evolved into a socio-technical infrastructure that shapes public attention, social interaction, and information governance. Understanding how user engagement behaviors, such as retweets, comments, and likes, collectively influence information diffusion is importa…
Background The genesis of Parkinson’s disease (PD), a common central neurodegenerative disorder, involves dysregulation of protein posttranslational modifications (PTM). The primary objective of this study was to screen key PTM-associated genes (PTMGs) serving as diagnostic indic…
Bio-logging is a popular method for data collection in animal research, especially for hard-to-observe animals. Newer bio-logger generations utilise WiFi technology, enabling researchers to collect high-resolution data at the cost of higher energy expenditure of the devices. In t…