Few-shot learning for facial expression recognition: a comprehensive survey
CL Kim, BG Kim - Journal of Real-Time Image Processing, 2023 - Springer
Facial expression recognition (FER) is utilized in various fields that analyze facial
expressions. FER is attracting increasing attention for its role in improving the convenience …
expressions. FER is attracting increasing attention for its role in improving the convenience …
When foundation model meets federated learning: Motivations, challenges, and future directions
The intersection of the Foundation Model (FM) and Federated Learning (FL) provides mutual
benefits, presents a unique opportunity to unlock new possibilities in AI research, and …
benefits, presents a unique opportunity to unlock new possibilities in AI research, and …
Low-parameter federated learning with large language models
We study few-shot Natural Language Understanding (NLU) tasks with Large Language
Models (LLMs) in federated learning (FL) scenarios. It is a challenging task due to limited …
Models (LLMs) in federated learning (FL) scenarios. It is a challenging task due to limited …
Facial expression recognition through multi-level features extraction and fusion
Y Xie, W Tian, H Zhang, T Ma - Soft Computing, 2023 - Springer
Recent studies have shown that deep learning has presented great potential in facial
expression recognition (FER) tasks and attracted more and more researchers' attention …
expression recognition (FER) tasks and attracted more and more researchers' attention …
Toward green and human-like artificial intelligence: A complete survey on contemporary few-shot learning approaches
Despite deep learning's widespread success, its data-hungry and computationally
expensive nature makes it impractical for many data-constrained real-world applications …
expensive nature makes it impractical for many data-constrained real-world applications …
Fewfedweight: Few-shot federated learning framework across multiple nlp tasks
Massively multi-task learning with large language models has recently made substantial
progress on few-shot generalization. However, this is usually performed in a centralized …
progress on few-shot generalization. However, this is usually performed in a centralized …
Federated few-shot learning for cough classification with edge devices
Automatically classifying cough sounds is one of the most critical tasks for the diagnosis and
treatment of respiratory diseases. However, collecting a huge amount of labeled cough …
treatment of respiratory diseases. However, collecting a huge amount of labeled cough …
[PDF][PDF] FedIris: Towards More Accurate and Privacy-Preserving Iris Recognition via Federated Template Communication
As biometric data undergo rapidly growing privacy concerns, building large-scale datasets
has become more difficult. Unfortunately, current iris databases are mostly in small scale, eg …
has become more difficult. Unfortunately, current iris databases are mostly in small scale, eg …
Federated Learning for Computer Vision
Computer Vision (CV) is playing a significant role in transforming society by utilizing
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …
machine learning (ML) tools for a wide range of tasks. However, the need for large-scale …
Privacy-preserving split learning for large-scaled vision pre-training
Z Wang, G Yang, H Dai, C Rong - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The growing concerns about data privacy in society lead to restrictions on the computer
vision research gradually. Several collaboration-based vision learning methods have …
vision research gradually. Several collaboration-based vision learning methods have …