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- Deep learning for sensor-based activity recognition: A survey2,000
The recent advance of deep learning based sensor-based activity recognition is surveyed from three aspects: sensor modality, deep model, and application and detailed insights on existing work are presented and grand challenges for future research are proposed.
- Generalizing to Unseen Domains: A Survey on Domain Generalization1,906
This paper provides a formal definition of domain generalization and discusses several related fields, and categorizes recent algorithms into three classes: data manipulation, representation learning, and learning strategy, and presents several popular algorithms in detail for each category.
- FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare999
FedHealth is proposed, the first federated transfer learning framework for wearable healthcare that performs data aggregation through federated learning, and then builds relatively personalized models by transfer learning.
- Weighted extreme learning machine for imbalance learning743
A weighted ELM which is able to deal with data with imbalanced class distribution while maintain the good performance on well balanced data as unweighted ELM and generalized to cost sensitive learning.
- 710
- Visual Domain Adaptation with Manifold Embedded Distribution Alignment657
This paper proposes a Manifold Embedded Distribution Alignment (MEDA) approach, which learns a domain-invariant classifier in Grassmann manifold with structural risk minimization, while performing dynamic distribution alignment to quantitatively account for the relative importance of marginal and conditional distributions.
- Balanced Distribution Adaptation for Transfer Learning589
This paper proposes a novel transfer learning approach, named as Balanced Distribution Adaptation (BDA), which can adaptively leverage the importance of the marginal and conditional distribution discrepancies, and several existing methods can be treated as special cases of BDA.
- Transfer Learning with Dynamic Adversarial Adaptation Network401
This paper proposes a novel Dynamic Adversarial Adaptation Network (DAAN) to dynamically learn domain-invariant representations while quantitatively evaluate the relative importance of global and local domain distributions.
- Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals368
A novel deep learning-based anomaly detection algorithm called CAE-M, which builds a Deep Convolutional Autoencoder to characterize spatial dependence of multi-sensor data with a Maximum Mean Discrepancy (MMD) and a Memory Network consisting of linear and non-linear predictions to capture temporal dependence from time-series data.
- 299
- A Pervasive Approach to EEG‐Based Depression Detection288
This study proves the feasibility of a pervasive three-electrode EEG acquisition system for depression diagnosis and suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression.
- 264
- Stratified Transfer Learning for Cross-domain Activity Recognition253
The proposed framework, referred to as Stratified Transfer Learning (STL), can dramatically improve the classification accuracy for cross-domain activity recognition and extensively investigate the performance of STL across different degrees of similarities and activity levels between domains.
- A Chinese sign language recognition system based on SOFM/SRN/HMM173
This paper uses the self-organizing feature maps (SOFM) as different signers' feature extractor for continuous hidden Markov models (HMM) so as to transform input signs into significant and low-dimensional representations that can be well modeled by the emission probabilities of HMM.
- Mitigating Herding in Hierarchical Crowdsourcing Networks171
A Lyapunov optimization based decision support approach - the Reputation-aware Task Sub-delegation approach with dynamic worker effort Pricing (RTS-P) - with objective functions aiming to achieve superlinear time-averaged collective productivity in an HCN.
- Easy Transfer Learning By Exploiting Intra-Domain Structures168
This paper proposes a practically Easy Transfer Learning (EasyTL) approach which requires no model selection and hyperparameter tuning, while achieving competitive performance and satisfies the Occam's Razor principle.
- Cross-people mobile-phone based activity recognition161
This work proposes an algorithm known as TransEMDT (Transfer learning EMbedded Decision Tree) that integrates a decision tree and the k-means clustering algorithm for personalized activity-recognition model adaptation and shows that this algorithm outperforms several traditional baseline algorithms.
- Near-infrared fluorescence-based multiplex lateral flow immunoassay for the simultaneous detection of four antibiotic residue families in milk158
A novel near-infrared fluorescence based multiplex lateral flow immunoassay by conjugating a near- Infrared label to broad-specificity monoclonal antibody/receptor as detection complexes is developed for rapidly screening the four families of antibiotic residues in milk.
- GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model154
GeneCompass is developed, the first knowledge-informed, cross-species foundation model pre-trained on an extensive dataset of over 120 million single-cell transcriptomes from human and mouse, which marks a milestone in advancing knowledge of universal gene regulatory mechanisms and accelerating the discovery of key cell fate regulators and candidate targets for drug development.
- Domain-invariant Feature Exploration for Domain Generalization149
It is argued that domain-invariant features should be originating from both internal and mutual sides, and DIFEX for Domain-Invariant Feature EXploration is proposed, which achieves state-of-the-art performance.
- Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application148
A thorough survey from three aspects: method, evaluation, and application, exploring knowledge distillation techniques tailored specifically for LLMs is presented, dividing the methods into white-box KD and black-box KD to better illustrate their differences.
- Deep Transfer Learning for Cross-domain Activity Recognition148
An effective Unsupervised Source Selection algorithm for Activity Recognition (USSAR) that is able to select the most similar K source domains from a list of available domains is proposed and an effective Transfer Neural Network to perform knowledge transfer for Activity recognition (TNNAR).
- Development and optimization of a multiplex lateral flow immunoassay for the simultaneous determination of three mycotoxins in corn, rice and peanut136
A multiplex lateral flow immunoassay developed for the simultaneous on-site determination of three mycotoxins (aflatoxin B1, zearalenone and ochratoxin A) in corn, rice and peanut demonstrated that it can be used for routine monitoring of mycotoxin contamination.
- 133
- Adaptive Memory Networks With Self-Supervised Learning for Unsupervised Anomaly Detection130
A novel approach called Adaptive Memory Network with Self-supervised Learning (AMSL) is proposed to address challenges and enhance the generalization ability in unsupervised anomaly detection and is significantly improves the performance compared to other state-of-the-art methods.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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