A review of automatic recognition technology for bird vocalizations in the deep learning era
Birds are considered critical indicators of ecosystem condition. Automatic recording devices
have emerged as a trending tool to assist field observations, contributing to biodiversity …
have emerged as a trending tool to assist field observations, contributing to biodiversity …
Artificial intelligence in salivary biomarker discovery and validation for oral diseases
Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and
maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which …
maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which …
Hierarchical graph transformer with contrastive learning for protein function prediction
Motivation In recent years, high-throughput sequencing technologies have made large-scale
protein sequences accessible. However, their functional annotations usually rely on low …
protein sequences accessible. However, their functional annotations usually rely on low …
Prior knowledge-embedded meta-transfer learning for few-shot fault diagnosis under variable operating conditions
In recent years, intelligent fault diagnosis based on deep learning has achieved vigorous
development thanks to its powerful feature representation ability. However, scarcity of high …
development thanks to its powerful feature representation ability. However, scarcity of high …
ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network
Graph Comparative Learning (GCL) is a self-supervised method that combines the
advantages of Graph Convolutional Networks (GCNs) and comparative learning, making it …
advantages of Graph Convolutional Networks (GCNs) and comparative learning, making it …
Selflre: Self-refining representation learning for low-resource relation extraction
Low-resource relation extraction (LRE) aims to extract potential relations from limited
labeled corpus to handle the problem of scarcity of human annotations. Previous works …
labeled corpus to handle the problem of scarcity of human annotations. Previous works …
Context or knowledge is not always necessary: A contrastive learning framework for emotion recognition in conversations
Emotion recognition in conversations (ERC) aims to detect the emotion of utterances in
conversations. Existing efforts generally focus on modeling context-and knowledge-sensitive …
conversations. Existing efforts generally focus on modeling context-and knowledge-sensitive …
MixStyle-Based Contrastive Test-Time Adaptation: Pathway to Domain Generalization
K Yamashita, K Hotta - … of the IEEE/CVF Conference on …, 2024 - openaccess.thecvf.com
Recent advancements in domain generalization have increasingly focused on Test-time
Adaptation (TTA) which adapts models to unknown domains during testing. Test-time …
Adaptation (TTA) which adapts models to unknown domains during testing. Test-time …
Trigger-free cybersecurity event detection based on contrastive learning
M Tang, Y Guo, Q Bai, H Zhang - The Journal of Supercomputing, 2023 - Springer
Cybersecurity event detection aims to detect and classify the occurrence of cybersecurity
events from a large amount of data. Previous approaches to event detection have used …
events from a large amount of data. Previous approaches to event detection have used …
Artificial intelligence algorithms in flood prediction: a general overview
M Pandey - Geo-information for Disaster Monitoring and …, 2024 - Springer
This paper presents a comprehensive general overview of the extensive literature available
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …