[HTML][HTML] A systematic survey on multimodal emotion recognition using learning algorithms
Emotion recognition is the process to detect, evaluate, interpret, and respond to people's
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
Meta-health: learning-to-learn (Meta-learning) as a next generation of deep learning exploring healthcare challenges and solutions for rare disorders: a systematic …
K Singh, D Malhotra - Archives of Computational Methods in Engineering, 2023 - Springer
In clinical scenarios, the two subfields of Artificial Intelligence (AI), ie, Machine Learning (ML)
and Deep Learning (DL) methods have become the de facto standard in several domains of …
and Deep Learning (DL) methods have become the de facto standard in several domains of …
SSL-ProtoNet: Self-supervised Learning Prototypical Networks for few-shot learning
Few-shot learning is seeking to generalize well to unseen tasks with insufficient labeled
samples. Existing works have achieved generalization by exploring inter-class …
samples. Existing works have achieved generalization by exploring inter-class …
Structural digital Twin for damage detection of CFRP composites using meta transfer Learning-based approach
C Liu, Y Chen, X Xu - Expert Systems with Applications, 2025 - Elsevier
Using deep learning approaches to identify and locate defects in composite structures made
of Carbon Fiber Reinforced Plastics (CFRP) is becoming increasingly popular. However …
of Carbon Fiber Reinforced Plastics (CFRP) is becoming increasingly popular. However …
Self-supervised human mobility learning for next location prediction and trajectory classification
Massive digital mobility data are accumulated nowadays due to the proliferation of location-
based service (LBS), which provides the opportunity of learning knowledge from human …
based service (LBS), which provides the opportunity of learning knowledge from human …
Few-shot driver identification via meta-learning
L Lu, S Xiong - Expert Systems with Applications, 2022 - Elsevier
Driver identification in connected transportation is useful for usage-based insurance,
personalized assisted driving, fleet management etc. Capturing the driving style from data …
personalized assisted driving, fleet management etc. Capturing the driving style from data …
Few-shot learning for name entity recognition in geological text based on GeoBERT
Geological reports are records of the geological elements and survey contents found in
geological exploration, but it is difficult to extract useful concepts from such reports. In the …
geological exploration, but it is difficult to extract useful concepts from such reports. In the …
Identifying user geolocation with hierarchical graph neural networks and explainable fusion
Determining user geolocation from social media data is essential in various location-based
applications—from improved transportation/supply management, through providing …
applications—from improved transportation/supply management, through providing …
Simple but powerful, a language-supervised method for image emotion classification
Image emotion classification is an important computer vision task to extract emotions from
images. The methods for image emotion classification (IEC) are primarily based on label or …
images. The methods for image emotion classification (IEC) are primarily based on label or …
Smart epidermal electrophysiological electrodes: Materials, structures, and algorithms
Y Ye, H Wang, Y Tian, K Gao, M Wang… - Nanotechnology and …, 2023 - pubs.aip.org
Epidermal electrophysiological monitoring has garnered significant attention for its potential
in medical diagnosis and healthcare, particularly in continuous signal recording. However …
in medical diagnosis and healthcare, particularly in continuous signal recording. However …