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Sesamoiditis is a common equine disease with varying severity, leading to increased injury risks and performance degradation in horses. Accurate grading of sesamoiditis is crucial for effective treatment. Although deep learning-based approaches ...

• Innovative multi-task learning model grades sesamoiditis in equine radiographs with clinical interpretability.
• Dual-branch decoder and feature fusion improve grading accuracy by focusing on vascular channels.
• Visual and ...

The Broad Learning System (BLS) employs two successive random feature mappings and incorporates ridge regression to construct an efficient classifier. This system achieves performance comparable to Deep Neural Networks, while reducing ...

• Improving the Broad Learning System by ensemble learning and Shapley Value.
• Performing feature selection via their contribution and inner-collaboration.
• Proposed a stable data weight update method for imbalanced data ...

Laryngeal hemiplegia (LH) is a major upper respiratory tract (URT) complication in racehorses. Endoscopy imaging of horse throat is a gold standard for URT assessment. However, current manual assessment faces several challenges, stemming from the ...

• Emulating vet diagnostic procedures.
• Extracting clinically meaningful spatiotemporal features from YOLOv8 predictions.
• Transparent classification by Decision Tree.
• Providing Explainability related assessments.

In this paper, a multi-scale attention extraction siamese network metric model (SASNet) is proposed on the basis of an in-depth analysis of the relationship between similar and redundant data filtering. Based on the siamese network, the model integrates ...

Encrypted DNS protocols—DNS-over-TLS (DoT), DNS-over-HTTPS (DoH), and DNS-over-QUIC (DoQ), have been standardized and widely embraced by the industry to enhance the security and privacy of DNS transmissions. As more software and devices support ...

Group activity recognition aims to recognize holistic activity in multi-person scene, necessitating consideration of the interactions between actors and their surroundings. It has various applications, such as public surveillance, video analysis. ...

• A novel progressive network structure for group activity recognition.
• Context feature extraction strategy for the exploration of group activity.
• Capturing temporal and spatial dynamics by reasoning local–global GCN.

Local feature matching enjoys wide-ranging applications in the realm of computer vision, encompassing domains such as image retrieval, 3D reconstruction, and object recognition. However, challenges persist in improving the accuracy and robustness ...

• This endeavor is to furnish a comprehensive overview of local feature matching methods.
• We analyze various metrics used for performance evaluation of key local feature matching methods.
• We endeavor to outline the current challenges ...

Encrypted traffic classification is an important technique for network management and network security assurance. Current mainstream methods utilize machine learning and deep learning techniques for classification, and train models with complete ...

Remote sensing scene (RSS) image classification plays a vital role in various fields such as urban planning and environmental protection. However, due to higher inter-class similarity and intra-class variability, achieving accurate classification ...

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• Extracting pure kiwifruit canopy information improves SMC estimation effectively.
• The optimal band combination algorithm efficiently screens band and FVC variables.
• The ensemble learning model for estimating SMC at different root-...

Accurate and real-time monitoring of soil moisture content (SMC) is of utmost importance for effective field irrigation and maximizing crop water productivity. However, a comprehensive investigation into the inversion study for determining ...

Heterogeneous multiagent system (MAS) has been attracting increasing attention in many application areas, but the safety and reliability of MAS are still challenging issues. Fault diagnosis is a necessary technology to ensure the safety and reliability of ...

A novel hybrid active-passive reconfigurable intelligent surface (RIS) transmitter enabled downlink multi-user communication system is investigated. Specifically, RISs are exploited to serve as transmitter antennas, where each element can flexibly switch ...

Synthetic lethality (SL) occurs when the inactivation of two genes results in cell death while the inactivation of either gene alone is non-lethal. SL-based therapy has become a promising anti-cancer treatment option with the increasing ...

• Synthetic lethal interactions were predicted based on machine learning and statistic inference.
• Cancer-specific synthetic lethal interactions were screened using mutual exclusivity and differential expression.
• A freely available ...

Recently, CLIP has found practical utility in the domain of pixel-level zero-shot segmentation tasks. The present landscape features two-stage methodologies beset by issues such as intricate pipelines and elevated computational costs. While current one-...

Electronic health records (EHRs) contain diverse patient information, including medical notes, clinical events, and laboratory test results. Integrating this multimodal data can improve disease diagnoses using deep learning models. However, ...

• EHR-KnowGen integrates multimodal EHR data for disease diagnosis generation.
• External knowledge improves accuracy and interpretability of disease diagnoses.
• Encoding EHR modalities with large language models and soft prompts.
• ...

In the field of battery health state prognostics, the inaccurate lithium-ion battery's health status prediction is usually caused by the capacity regeneration (CR) phenomenon triggered by relaxation effects during the degradation process. To ...

Path algebras from quivers are a fundamental class of algebras with wide applications. Yet it is challenging to describe their universal properties since their underlying path semigroups are only partially defined. A new notion, called locality ...

The PBFT algorithm is a consensus algorithm that reduces communication complexity to a polynomial level, addressing the inefficiency of traditional Byzantine fault tolerance mechanisms. It is commonly adopted in the consensus layer of blockchain systems. ...

Accurate and effective channel state information (CSI) feedback is a key technology for massive multiple-input and multiple-output systems. Recently, deep learning (DL) has been introduced for CSI feedback enhancement through massive collected training ...

A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted simultaneous wireless information and power transfer (SWIPT) system is proposed. More particularly, an STAR-RIS is deployed to assist in the information/...