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Multiple token rearrangement Transformer network with explicit superpixel constraint for segmentation of echocardiography.
Med Image Anal
January 2025
General Hospital of the Southern Theatre Command, PLA, Guangzhou, China; The First School of Clinical Medicine, Southern Medical University, Guangzhou, China. Electronic address:
Diagnostic cardiologists have considerable clinical demand for precise segmentation of echocardiography to diagnose cardiovascular disease. The paradox is that manual segmentation of echocardiography is a time-consuming and operator-dependent task. Computer-aided segmentation can reduce the workflow greatly.
View Article and Find Full Text PDFCA-SQBG: Cross-attention guided Siamese quantum BiGRU for drug-drug interaction extraction.
Comput Biol Med
January 2025
College of Electronic Information, Xijing University, Xi'an, China. Electronic address:
Accurate and efficient drug-drug interaction extraction (DDIE) from the medical corpus is essential for pharmacovigilance, drug therapy and drug development. To solve the problems of unbalance dataset and lack of accurate manual annotations in DDIE, a cross-attention guided Siamese quantum BiGRU (CA-SQBG) is constructed to improve feature representation learning ability for DDIE. It mainly consists of two quantum BiGRUs (QBiGRUs) and a cross-attention, where two QBiGRUs are Siamese implemented in a variational quantum environment to learn the contextual semantic feature representation of drug pairs, cross-attention is employed to learn mutual information from the Siamese QBiGRUs, which in turn allows the two modules to extract DDI more collaboratively.
View Article and Find Full Text PDFMDA-DETR: Enhancing Offending Animal Detection with Multi-Channel Attention and Multi-Scale Feature Aggregation.
Animals (Basel)
January 2025
School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China.
Conflicts between humans and animals in agricultural and settlement areas have recently increased, resulting in significant resource loss and risks to human and animal lives. This growing issue presents a global challenge. This paper addresses the detection and identification of offending animals, particularly in obscured or blurry nighttime images.
View Article and Find Full Text PDFAttention-based interactive multi-level feature fusion for named entity recognition.
Sci Rep
January 2025
Nanfang College Guangzhou, Guangzhou, 510970, China.
Named Entity Recognition (NER) is an essential component of numerous Natural Language Processing (NLP) systems, with the aim of identifying and classifying entities that have specific meanings in raw text, such as person (PER), location (LOC), and organization (ORG). Recently, Deep Neural Networks (DNNs) have been extensively applied to NER tasks owing to the rapid development of deep learning technology. However, despite their advancements, these models fail to take full advantage of the multi-level features (e.
View Article and Find Full Text PDFLow-resource MobileBERT for emotion recognition in imbalanced text datasets mitigating challenges with limited resources.
PLoS One
January 2025
Department of Computer Science, GC Women University Sialkot, Sialkot, Pakistan.
Modern dialogue systems rely on emotion recognition in conversation (ERC) as a core element enabling empathetic and human-like interactions. However, the weak correlation between emotions and semantics poses significant challenges to emotion recognition in dialogue. Semantically similar utterances can express different types of emotions, depending on the context or speaker.
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