MMCAF: A Survival Status Prediction Method Based on Cross‐Attention Fusion of Multimodal Colorectal Cancer Data
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.70051
Abstract: The employment of artificial intelligence methods in computer‐assisted diagnosis systems is critical for colorectal cancer survival analysis and prognosis. However, due to the low prediction accuracy of single‐modal data research and the complexity of multimodal… read more here.
Keywords: colorectal cancer; cancer; fusion; cross attention ... See more keywords
A multimodal fusion network based on a cross-attention mechanism for the classification of Parkinsonian tremor and essential tremor
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-79111-w
Abstract: Parkinsonian tremor (PT) and Essential tremor (ET) exist as upper limb tremors in clinical practice. Notably, their types of trembling share similar presentations and overlapping frequencies. To enhance objectivity and efficiency in the diagnosis of… read more here.
Keywords: classification; cross attention; tremor; attention mechanism ... See more keywords
Screen shooting resistant watermarking based on cross attention
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-00912-8
Abstract: With the development of digital imaging devices, the process of recording sensitive information displayed on screens through mobile phones and cameras has become a prominent technique for modern data leaks. In order to identify the… read more here.
Keywords: screen; screen shooting; attention; cross attention ... See more keywords
GTAT: empowering graph neural networks with cross attention
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-88993-3
Abstract: Graph Neural Networks (GNNs) serve as a powerful framework for representation learning on graph-structured data, capturing the information of nodes by recursively aggregating and transforming the neighboring nodes’ representations. Topology in graph plays an important… read more here.
Keywords: information; attention; graph neural; cross attention ... See more keywords
FMCA-DTI: a fragment-oriented method based on a multihead cross attention mechanism to improve drug–target interaction prediction
Sign Up to like & getrecommendations! Published in 2024 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btae347
Abstract: Abstract Motivation Identifying drug–target interactions (DTI) is crucial in drug discovery. Fragments are less complex and can accurately characterize local features, which is important in DTI prediction. Recently, deep learning (DL)-based methods predict DTI more… read more here.
Keywords: multihead cross; dti; cross attention; fmca dti ... See more keywords
ICAN: Interpretable cross-attention network for identifying drug and target protein interactions
Sign Up to like & getrecommendations! Published in 2022 at "PLOS ONE"
DOI: 10.1101/2022.08.04.502877
Abstract: Drug–target protein interaction (DTI) identification is fundamental for drug discovery and drug repositioning, because therapeutic drugs act on disease-causing proteins. However, the DTI identification process often requires expensive and time-consuming tasks, including biological experiments involving… read more here.
Keywords: cross attention; interpretable cross; attention; drug ... See more keywords
CAMM: Cross-Attention Multimodal Classification of Disaster-Related Tweets
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3202976
Abstract: During the past decade, social media platforms have been extensively used for information dissemination by the affected community and humanitarian agencies during a disaster. Although many studies have been done recently to classify the informative… read more here.
Keywords: camm; cross attention; disaster; deep learning ... See more keywords
C2I-CAT: Class-to-Image Cross Attention Transformer for Out-of-Distribution Detection
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3391808
Abstract: In our work, we have empirically found that Vision Transformer (ViT) could not extract object-centric features when applied to out-of-distribution (OOD) detection. To make object-centric attention, we design an additional module that employs a cross-attention… read more here.
Keywords: detection; distribution; attention; cross attention ... See more keywords
Enhancing Emotion Recognition in Speech Based on Self-Supervised Learning: Cross-Attention Fusion of Acoustic and Semantic Features
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3554454
Abstract: Speech Emotion Recognition has gained considerable attention in speech processing and machine learning due to its potential applications in human-computer interaction, mental health monitoring, and customer service. However, state-of-the-art models for speech emotion recognition use… read more here.
Keywords: cross attention; emotion recognition; speech;
HSIF: A Transformer-Based Cross-Attention Framework for Cryptocurrency Trend Forecasting via Multimodal Sentiment–Market Fusion
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3605522
Abstract: Cryptocurrency markets are highly volatile and sentiment-driven, posing challenges to traditional forecasting methods. This paper presents Hard and Soft Information Fusion (HSIF), a novel Transformer-based dual-stream model that combines market data and social sentiment using… read more here.
Keywords: fusion; cross attention; transformer based; sentiment ... See more keywords
Identification of Pandemic Risk for Avian Influenza Virus with Graph Cross Attention Networks.
Sign Up to like & getrecommendations! Published in 2025 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2025.3625980
Abstract: Influenza A virus poses a significant threat to global health due to its high mutability and potential for pandemics. Accurate prediction of influenza virus pandemic risk can mitigate their threat to public health systems and… read more here.
Keywords: risk; cross attention; virus; graph cross ... See more keywords