Transformers in vision: A survey

S Khan, M Naseer, M Hayat, SW Zamir… - ACM computing …, 2022 - dl.acm.org
Astounding results from Transformer models on natural language tasks have intrigued the
vision community to study their application to computer vision problems. Among their salient …

[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom

T Shaik, X Tao, L Li, H Xie, JD Velásquez - Information Fusion, 2023 - Elsevier
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

[HTML][HTML] A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications

L Alzubaidi, J Bai, A Al-Sabaawi, J Santamaría… - Journal of Big Data, 2023 - Springer
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Multi-level feature fusion for multimodal human activity recognition in Internet of Healthcare Things

MM Islam, S Nooruddin, F Karray, G Muhammad - Information Fusion, 2023 - Elsevier
Abstract Human Activity Recognition (HAR) has become a crucial element for smart
healthcare applications due to the fast adoption of wearable sensors and mobile …

Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects

Y Feng, J Chen, J Xie, T Zhang, H Lv, T Pan - Knowledge-Based Systems, 2022 - Elsevier
The advances of intelligent fault diagnosis in recent years show that deep learning has
strong capability of automatic feature extraction and accurate identification for fault signals …

Is attention explanation? an introduction to the debate

A Bibal, R Cardon, D Alfter, R Wilkens… - Proceedings of the …, 2022 - aclanthology.org
The performance of deep learning models in NLP and other fields of machine learning has
led to a rise in their popularity, and so the need for explanations of these models becomes …

Imbalance fault diagnosis under long-tailed distribution: Challenges, solutions and prospects

Z Chen, J Chen, Y Feng, S Liu, T Zhang… - Knowledge-Based …, 2022 - Elsevier
Intelligent fault diagnosis based on deep learning has yielded remarkable progress for its
strong feature representation capability in recent years. Nevertheless, in engineering …

Attention-based Feature Fusion Generative Adversarial Network for yarn-dyed fabric defect detection

H Zhang, G Qiao, S Lu, L Yao… - Textile Research …, 2023 - journals.sagepub.com
Defects on the surface of yarn-dyed fabrics are one of the important factors affecting the
quality of fabrics. Defect detection is the core link of quality control. Due to the diversity of …

Spatial correlation and temporal attention-based LSTM for remaining useful life prediction of turbofan engine

H Tian, L Yang, B Ju - Measurement, 2023 - Elsevier
Remaining useful life (RUL) prediction has always been a core task of prognostics and
health management technology, which is crucial to the reliable and safe operation of …

[HTML][HTML] An outlook into the future of egocentric vision

C Plizzari, G Goletto, A Furnari, S Bansal… - International Journal of …, 2024 - Springer
What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …