Transfer learning for activity recognition: a survey

LIBSVM: A library for support vector machines

Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918

A survey on transfer learning

Pan, S. J., & Yang, Q. (2010) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2009.191 · Cited by 23,387

A decision-theoretic generalization of on-line learning and an application to boosting

Freund, Y., & Schapire, R. E. (1997) · Journal of Computer and System Sciences · doi:10.1006/jcss.1997.1504 · Cited by 20,466

Advances in Neural Information Processing Systems 19

(2007) · The MIT Press eBooks · doi:10.52202/085713 · Cited by 16,043

A Global Geometric Framework for Nonlinear Dimensionality Reduction

Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science · doi:10.1126/science.290.5500.2319 · Cited by 13,585

Mining sequential patterns

Agrawal, R., & Srikant, R. (2002) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.1995.380415 · Cited by 5,150

Domain Adaptation via Transfer Component Analysis

Pan, S. J., Tsang, I. W.-H., Kwok, J. T.-Y., & Yang, Q. (2010) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2010.2091281 · Cited by 4,809

Activity recognition using cell phone accelerometers

Kwapisz, J. R., Weiss, G. M., & Moore, S. A. (2011) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1964897.1964918 · Cited by 2,912 · cited 1×

When and where do we apply what we learn?: A taxonomy for far transfer

Barnett, S. M., & Ceci, S. J. (2002) · Psychological Bulletin · doi:10.1037/0033-2909.128.4.612 · Cited by 2,076 · cited 1×

The foundations of cost-sensitive learning

Elkan, C. (2001) · Cited by 1,945

Transfer Learning in Earth Observation Data Analysis: A review

Nowakowski, A., Rosso, M. P. D., Zachar, P., Spiller, D., Gabara, G., Barretta, D., Kalinowska, K. B., Choromański, K., Wilkowski, A., Sebastianelli, A., et al. (2024) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2024.3494673 · Cited by 17

Personalized Activity Recognition Using Partially Available Target Data

Fallahzadeh, R., Ashari, Z. E., Alinia, P., & Ghasemzadeh, H. G. (2021) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2021.3071434 · Cited by 16

DeepTransHAR: a novel clustering-based transfer learning approach for recognizing the cross-domain human activities using GRUs (Gated Recurrent Units) Networks

Kumar, P., & Suresh, S. (2023) · Internet of Things · doi:10.1016/j.iot.2023.100681 · Cited by 17

Unsupervised domain adaptation without source data for estimating occupancy and recognizing activities in smart buildings

Dridi, J., Amayri, M., & Bouguila, N. (2023) · Energy and Buildings · doi:10.1016/j.enbuild.2023.113808 · Cited by 16

Activity recognition in manual manufacturing: Detecting screwing processes from sensor data

Günther, L. C., Kärcher, S., & Bauernhansl, T. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.288 · Cited by 16

Transfer learning for smart construction: Advances and future directions

Yu, G., Xu, X., Yiu, T. W., & Wang, J. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.106238 · Cited by 17

Transfer Learning with Prior Data-Driven Models from Multiple Unconventional Fields

Cornelio, J., Razak, S. M., Cho, Y., Liu, H., Vaidya, R. N., & Jafarpour, B. (2023) · SPE Journal · doi:10.2118/214312-pa · Cited by 15

Online Bayesian Transfer Learning for Sequential Data Modeling

Jaini, P., Chen, Z., Carbajal, P., Law, E., Middleton, L. E., Regan, K., Schaekermann, M., Trimponias, G., Tung, J. Y., & Poupart, P. (2017) · International Conference on Learning Representations · Cited by 15

Weakly Supervised Instance Segmentation Based on Two-Stage Transfer Learning

Sun, Y., Liao, S., Gao, C., Xie, C., Yang, F., Zhao, Y., & Sagata, A. (2020) · IEEE Access · doi:10.1109/access.2020.2969480 · Cited by 14

A Signal-Level Transfer Learning Framework for Autonomous Reconfiguration of Wearable Systems

Saeedi, R., & Gebremedhin, A. H. (2018) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2018.2878673 · Cited by 15

Collaborative learning based on centroid-distance-vector for wearable devices

Kong, D., Bao, Y., & Chen, W. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.105569 · Cited by 15

A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive FusionPreprint

Chen, R., Guo, Y., Zheng, H., & Jiang, H. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.01800 · Cited by 18

MICAR: multi-inhabitant context-aware activity recognition in home environments

Arrotta, L., Bettini, C., & Civitarese, G. (2022) · Distributed and Parallel Databases · doi:10.1007/s10619-022-07403-z · Cited by 14

Prediction of buffeting responses of the thin plate under joint action of wave and wind using LSTM and transfer learning

Hu, P., Cheng, W., Xu, G., Han, Y., Yan, N., & Wang, N. (2023) · Applied Ocean Research · doi:10.1016/j.apor.2023.103514 · Cited by 14

Combining Public Human Activity Recognition Datasets to Mitigate Labeled Data Scarcity

Presotto, R., Ek, S., Civitarese, G., Portet, F., Lalanda, P., & Bettini, C. (2023) · IEEE International Conference on Smart Computing · doi:10.1109/smartcomp58114.2023.00022 · Cited by 16

Heterogeneous transfer learning: recent developments, applications, and challenges

Khan, S. A., Yin, P., Guo, Y., Asim, M., & El‐Latif, A. A. A. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18352-3 · Cited by 14

Using additional training sensors to improve single-sensor complex activity recognition

Lago, P., Matsuki, M., Adachi, K., & Inoue, S. (2021) · International Symposium on Wearable Computers · doi:10.1145/3460421.3480421 · Cited by 14

Local and Global Alignments for Generalizable Sensor-Based Human Activity Recognition

Wang, L., Wang, J., & Chen, Y. (2022) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp43922.2022.9747363 · Cited by 14

A CNN Based Transfer Learning Model for Automatic Activity Recognition from Accelerometer Sensors

Chikhaoui, B., Gouineau, F., & Sotir, M. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-96133-0_23 · Cited by 14

Robust Finger Interactions with COTS Smartwatches via Unsupervised Siamese Adaptation

Chen, W., Wang, Z., Quan, P., Peng, Z., Lin, S., Srivastava, M. B., Matusik, W., & Stankovic, J. A. (2023) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3586183.3606794 · Cited by 13

Sensor Data Based Models for Workforce Management in Smart Manufacturing

Alamin, A., Tao, W., Qin, R., & Leu, M.-C. (2018) · Cited by 13

Predicting Sensor Events, Activities, and Time of Occurrence Using Binary Sensor Data From Homes With Older Adults

Casagrande, F. D., Torresen, J., & Zouganeli, E. (2019) · IEEE Access · doi:10.1109/access.2019.2933994 · Cited by 13

Supervised Domain Adaptation using Graph Embedding

Hedegaard, L., Sheikh-Omar, O. A., & Iosifidis, A. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412422 · Cited by 15

Facilitating Human Activity Data Annotation via Context-Aware Change Detection on Smartwatches

Akbari, A., Martinez, J., & Jafari, R. (2021) · ACM Transactions on Embedded Computing Systems · doi:10.1145/3431503 · Cited by 13

A Survey of Vision-Based Transfer Learning in Human Activity Recognition

Adama, D. A., Lotfi, A., & Ranson, R. M. (2021) · Electronics · doi:10.3390/electronics10192412 · Cited by 13

Tackling stain variability using CycleGAN-based stain augmentation

Bouteldja, N., Hölscher, D. L., Bülow, R. D., Roberts, I. S. D., Coppo, R., & Boor, P. (2022) · Journal of Pathology Informatics · doi:10.1016/j.jpi.2022.100140 · Cited by 14

Domain Adaptation with Representation Learning and Nonlinear Relation for Time Series

Hussein, A., & Hajj, H. M. (2022) · ACM Trans. Internet Things · doi:10.1145/3502905 · Cited by 15

Benchmarking Domain Adaptation Methods on Aerial Datasets

Nagananda, N., Taufique, A. M. N., Madappa, R., Jahan, C. S., Minnehan, B., Rovito, T. V., & Savakis, A. E. (2021) · Sensors · doi:10.3390/s21238070 · Cited by 12

Graph-Based Semi-Supervised Learning for Activity Labeling in Health Smart Home

Hu, Y., Wang, B., Sun, Y., An, J., & Wang, Z. (2020) · IEEE Access · doi:10.1109/access.2020.3033589 · Cited by 12

A user-guided personalization methodology to facilitate new smart home occupancy

Ali, S. M., Augusto, J. C., Windridge, D., & Ward, E. V. (2022) · Universal Access in the Information Society · doi:10.1007/s10209-022-00883-x · Cited by 12

AI-Assisted Food Intake Activity Recognition Using 3D mmWave Radars

Wu, Y., Chen, Y., Shirmohammadi, S., & Hsu, C.-H. (2022) · doi:10.1145/3552484.3555753 · Cited by 12

Label Propagation

Rey, V. F., & Lukowicz, P. (2017) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3130959 · Cited by 12

Reasoning with smart objects’ affordance for personalized behavior monitoring in pervasive information systems

Matassa, A., & Riboni, D. (2019) · Knowledge and Information Systems · doi:10.1007/s10115-019-01357-y · Cited by 12

Identification of Bicycling Periods Using the MicroPEM Personal Exposure Monitor

Chew, R., Thornburg, J. W., Jack, D. W., Smith, C., Yang, Q., & Chillrud, S. N. (2019) · Sensors · doi:10.3390/s19214613 · Cited by 12

Activity Recognition in New Smart Home Environments

Wang, W., & Miao, C. (2018) · International Workshop on Multimedia for Personal Health and Health Care (MMHealth) · doi:10.1145/3264996.3265001 · Cited by 14

Personality Trait Detection via Transfer Learning

Alshouha, B., Serrano‐Guerrero, J., Chiclana, F., Romero, F. P., & Olivas, J. Á. (2024) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.046711 · Cited by 12

Back‐dropout transfer learning for action recognition

Ren, H., Kanhabua, N., Møgelmose, A., Liu, W., Kulkarni, K., Escalera, S., Baró, X., & Moeslund, T. B. (2018) · IET Computer Vision · doi:10.1049/iet-cvi.2016.0309 · Cited by 11

Design and Development of Granular Fuzzy Rule-Based Models for Knowledge Transfer

Zhu, X., Wang, D., Pedrycz, W., & Li, Z. (2022) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2022.3184716 · Cited by 11

Activity Recognition in Individuals Walking With Assistive Devices: The Benefits of Device-Specific Models

Lonini, L., Gupta, A. N., Deems-Dluhy, S., Hoppe-Ludwig, S., Kording, K. P., & Jayaraman, A. (2017) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/rehab.7317 · Cited by 11

Automated quantification of DNA damage via deep transfer learning based analysis of comet assay images

Namuduri, S., Narayanan, B. N., Karbaschi, M., Cooke, M. S., & Bhansali, S. (2019) · SPIE Applications of Machine Learning · doi:10.1117/12.2529352 · Cited by 11

DistractNet: a deep convolutional neural network architecture for distracted driver classification

Nasri, I., Karrouchi, M., Snoussi, H., Kassmi, K., & Messaoudi, A. (2022) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v11.i2.pp494-503 · Cited by 13

Homogeneous Transfer Active Learning for Time Series Classification

Gikunda, P., & Jouandeau, N. (2021) · International Conference on Machine Learning and Applications · doi:10.1109/icmla52953.2021.00129 · Cited by 11

Robust transfer learning of high-dimensional generalized linear model

Sun, F., & Zhang, Q. (2023) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2023.128674 · Cited by 10

Semi-Supervised Adversarial Auto-Encoder to Expedite Human Activity Recognition

Thapa, K., Seo, Y., Yang, S., & Kim, K. (2023) · Sensors · doi:10.3390/s23020683 · Cited by 11

Data Analytics for Pervasive Health

Acampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2015) · Cited by 10

Transfer metric learning for action similarity using high-level semantics

Al-Halah, Z., Rybok, L., & Stiefelhagen, R. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2015.07.005 · Cited by 10

Sensor-based activity recognition via learning from distributions

Qian, H. (2019) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/137691 · Cited by 9

Uncovering the Connections Between Adversarial Transferability and Knowledge TransferabilityPreprint

Liang, K., Zhang, J. Y., Wang, B., Yang, Z., Koyejo, S., & Li, B. H. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.14512 · Cited by 10

Enhancing surface water quality prediction in data-scarce sites using transfer learning and neural networks

Liao, Z., Wang, X., Tian, W., & Xie, W. (2025) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2025.107923 · Cited by 9

STAR: A Scalable Self-taught Learning Framework for Older Adults’ Activity Recognition

Ramamurthy, S. R., Ghosh, I., Gangopadhyay, A., Galik, E. M., & Roy, N. (2021) · IEEE International Conference on Smart Computing · doi:10.1109/smartcomp52413.2021.00037 · Cited by 9

EarBender: Enabling Rich IMU-based Natural Hand-to-Ear Interaction in Commodity Earables

Alkiek, K., Youssef, M. A., & Harras, K. A. (2023) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3594739.3610671 · Cited by 11

What to Transfer? High-Level Semantics in Transfer Metric Learning for Action Similarity

Al-Halah, Z., Rybok, L., & Stiefelhagen, R. (2014) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2014.478 · Cited by 9

Supervised heterogeneous transfer learning using random forests

Sukhija, S., Krishnan, N. C., & Kumar, D. (2018) · Joint International Conference on Data Science & Management of Data (CODS-COMAD) · doi:10.1145/3152494.3152510 · Cited by 9

Collaborative Multi-Expert Active Learning for Mobile Health Monitoring: Architecture, Algorithms, and Evaluation

Saeedi, R., Sasani, K., & Gebremedhin, A. H. (2020) · Sensors · doi:10.3390/s20071932 · Cited by 9

Multi-convLSTM neural network for sensor-based human activity recognition

Li, Z., Liu, Y., Guo, X., & Zhang, J. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1682/1/012062 · Cited by 9

Research on Personal Credit Risk Assessment Model Based on Instance-Based Transfer Learning

Wang, M., & Yang, H. (2021) · International Journal of Intelligence Science · doi:10.4236/ijis.2021.111004 · Cited by 9

A recent survey of heterogeneous transfer learning

Bao, R., Sun, Y., Gao, Y., Li, J., Yang, Q., Wang, J., Yang, Q., Mao, Z., Song, C., Ren, A., et al. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.116577 · Cited by 31

ActiLabel: A Combinatorial Transfer Learning Framework for Activity RecognitionPreprint

Alinia, P., Mirzadeh, S. I., & Ghasemzadeh, H. G. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.07415 · Cited by 9

SciReviewGen: A Large-scale Dataset for Automatic Literature Review Generation

Kasanishi, T., Isonuma, M., Mori, J., & Sakata, I. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.418 · Cited by 16

Adversarial AI applied to cross-user inter-domain and intra-domain adaptation in human activity recognition using wireless signals

Hassan, M. A., Kelsey, T., & Rahman, F. (2024) · PLoS ONE · doi:10.1371/journal.pone.0298888 · Cited by 8

Automatic identification of the endangered hawksbill sea turtle behavior using deep learning and cross-species transfer learning

Jeantet, L., Zondo, K., Delvenne, C., Martin, J., Chevallier, D., & Dufourq, E. (2024) · Journal of Experimental Biology · doi:10.1242/jeb.249232 · Cited by 8

Language of actions: A generative model for activity recognition and next move prediction from motion sensors

Oğul, H. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125947 · Cited by 8

A Deep Learning-Based Model for the Automated Assessment of the Activity of a Single Worker

Patalas‐Maliszewska, J., & Halikowski, D. (2020) · Sensors · doi:10.3390/s20092571 · Cited by 8

Human activity recognition and classification using of convolutional neural networks and recurrent neural networks

Albaba, M., Qassab, A., & Yılmaz, A. (2020) · International Journal of Applied Mathematics Electronics and Computers · doi:10.18100/ijamec.803105 · Cited by 8

Deep Learning Applications

Mazzeo, P. L., & Spagnolo, P. (2021) · IntechOpen eBooks · doi:10.5772/intechopen.91576 · Cited by 8

Research on reinforcement learning-based safe decision-making methodology for multiple unmanned aerial vehicles

Yue, L., Yang, R., Zhang, Y., & Zuo, J. (2023) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2022.1105480 · Cited by 8

Derin Evrişimli Sinir Ağları Kullanılarak Pirinç Hastalıklarının Sınıflandırılması

Veziroglu, E., Paçal, İ., & Coşkunçay, A. (2023) · Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi · doi:10.21597/jist.1265769 · Cited by 8

Domain Selection of Transfer Learning in Fuzzy Prediction Models

Zuo, H., Zhang, G., Pedrycz, W., & Jie Lu, B. (2019) · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzz-ieee.2019.8858992 · Cited by 8

Does Adversarial Transferability Indicate Knowledge TransferabilityPreprint

Liang, K., Zhang, J. Y., Koyejo, S., & Li, B. H. (2021) · arXiv (Cornell University) · Cited by 8

Af-CAN: Multimodal Emotion Recognition Method Based on Situational Attention Mechanism

Zhang, X., Wang, M., Zeng, X., & Zhuang, X. (2024) · IEEE Access · doi:10.1109/access.2024.3471613 · Cited by 7

Wearable sensors for classification of load-handling tasks with machine learning algorithms in occupational safety and health: a systematic literature review

Peters, M., Potthast, W., Wischniewski, S., & Komnik, I. (2025) · Ergonomics · doi:10.1080/00140139.2025.2486193 · Cited by 7

Advancing Corn Yield Mapping in Kenya Through Transfer Learning

Bohra, A., Nottmeyer, S., Ren, C., Chen, S., & Ma, Y. (2025) · Remote Sensing · doi:10.3390/rs17101717 · Cited by 7

Exploring an Open Data Initiative Ontology for Shareable Smart Environment Experimental Datasets

McChesney, I., Nugent, C., Rafferty, J., & Synnott, J. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67585-5_42 · Cited by 7

Improvement of semantic segmentation through transfer learning of multi-class regions with convolutional neural networks on supine and prone breast MRI images

Ham, S., Kim, M., Lee, S., Wang, C., Ko, B., & Kim, N. (2023) · Scientific Reports · doi:10.1038/s41598-023-33900-x · Cited by 7

Capacity estimation of Li-ion battery based on transformer-adversarial discriminative domain adaptation

Liu, X., Yang, C., Meng, Y., Zhu, J., & Duan, Y. (2023) · AIP Advances · doi:10.1063/5.0152038 · Cited by 7

DWOSC: Dynamic Weight Optimization and Smoothness Constraint for Sensor-Based Human Activity Recognition

Li, Y., Wu, J., Li, W., & Fang, A. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3366277 · Cited by 7

Deep learning—Accelerating Next Generation Performance Analysis Systems?

Brock, H. (2018) · Conference of the International Sports Engineering Association (ISEA) · doi:10.3390/proceedings2060303 · Cited by 7

Share-n-Learn

Rokni, S. A., & Ghasemzadeh, H. G. (2019) · ACM Transactions on Design Automation of Electronic Systems · doi:10.1145/3318044 · Cited by 7

Deep Learning for Sensor-Based Activity Recognition: Recent Trends

Ahad, M. A. R., Antar, A. D., & Ahmed, M. (2020) · Intelligent systems reference library · doi:10.1007/978-3-030-51379-5_9 · Cited by 6

Intelligent fault diagnosis for rotating machinery based on potential energy feature and adaptive transfer affinity propagation clustering

Li, M., Wang, Y., Chen, Z., & Zhao, J. (2021) · Measurement Science and Technology · doi:10.1088/1361-6501/abfef5 · Cited by 7

Analysis of Deep Transfer Learning Using DeepConvLSTM for Human Activity Recognition from Wearable Sensors

Kalabakov, S., Gjoreski, M., Gjoreski, H., & Gams, M. (2021) · Informatica · doi:10.31449/inf.v45i2.3648 · Cited by 8

Innovative Data Transmission and Routing Strategies of Wireless Body Area Sensor Networks: Taxonomy, Review, Issues and Constraints of State of the Art Contributions in Recent Literature

Reddy, R. A., & Ram, N. V. (2018) · International Journal of Engineering & Technology · doi:10.14419/ijet.v7i2.7.10925 · Cited by 7

User-Centred Evaluation for Machine Learning

Cambo, S. A., & Gergle, D. (2018) · Human-computer interaction series · doi:10.1007/978-3-319-90403-0_16 · Cited by 7

Research on AES Cryptographic Chip Electromagnetic Attack Based on Deep Transfer Learning

Cui, X., Zhang, H., & Wang, L. (2019) · IEEE International Symposium on Electromagnetic Compatibility · doi:10.1109/isemc48616.2019.8986117 · Cited by 7

Multichannel Symbolic Aggregate Approximation Intelligent Icons: Application for Activity Recognition

Pappa, L., Karvelis, P. S., Georgoulas, G., & Stylios, C. D. (2020) · IEEE Symposium Series on Computational Intelligence (SSCI) · doi:10.1109/ssci47803.2020.9308497 · Cited by 7

Human Activity Recognition Based on Transfer Learning

Pang, J. (2018) · Digital Commons - University of South Florida (University of South Florida) · Cited by 7

A systematic review of transfer learning in software engineering

Malhotra, R., & Meena, S. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19756-x · Cited by 7

Subspace and second-order statistical distribution alignment for cross-domain recognition of human hand motions

Kou, H., Shi, H., & Hai, Z. (2023) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-023-02150-z · Cited by 6

On-Device Semi-Supervised Activity Detection: A New Privacy-Aware Personalized Health Monitoring Approach

Roy, A., Dutta, H., Bhuyan, A. K., & Biswas, S. K. (2024) · Sensors · doi:10.3390/s24144444 · Cited by 6

Environment aware ADL recognition system based on decision tree and activity frame

Melo, N., & Lee, J. (2018) · Paladyn Journal of Behavioral Robotics · doi:10.1515/pjbr-2018-0011 · Cited by 6

Identification of the User's Habits based on Activity Information

Melo, N., Lee, J., & Suzuki, R. (2018) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2018.8593873 · Cited by 6

A privacy-preserving distributed transfer learning in activity recognition

Hashemian, M., Razzazi, F., Zarrabi, H., & Moin, M. (2019) · Telecommunication Systems · doi:10.1007/s11235-018-0534-1 · Cited by 6

Learning alternative ways of performing a task

Nieves, D., Ramírez-Quintana, M. J., Monserrat, C., Ferri, C., & Hernández‐Orallo, J. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113263 · Cited by 6

Transfer Learning in Optimization: Interpretable Self-Organizing Maps Driven Similarity Indices to Identify Candidate Source Functions

Ravichandran, S. S., Sekar, K., Ramanath, V., & Ramu, P. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120529 · Cited by 6

Activity Recognition Using Ubiquitous Sensors

Liang, Y., Zhou, X., Guo, B., & Yu, Z. (2013) · Advances in human and social aspects of technology book series · doi:10.4018/978-1-4666-4695-7.ch002 · Cited by 6

Personalized travel mode detection with smartphone sensors

Su, X., Yao, Y., He, Q., Lu, J., & Tong, H. (2017) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2017.8258065 · Cited by 6

Towards Personalized Learning in Mobile Sensing Systems

Jiang, W., Li, Q., Su, L., Miao, C., Gu, Q., & Xu, W. (2018) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs.2018.00040 · Cited by 6

DeepSQA

Xing, T., García, L. A. R., Cerutti, F., Kaplan, L., Preece, A. D., & Srivastava, M. B. (2021) · IEEE/ACM International Conference on Internet-of-Things Design and Implementation (IoTDI) · doi:10.1145/3450268.3453529 · Cited by 8

Myoelectric Control of a Biomimetic Robotic Hand Using Deep Learning Artificial Neural Network for Gesture Classification

Kashizadeh, A., Penan, K., Belford, A., Razmjou, A., & Asadnia, M. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3191640 · Cited by 6

Where are you?

Doğan, G., Cay, I., Ertas, S. S., Keskin, Ş. R., Alotaibi, N., & Sahin, E. (2020) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3410530.3414354 · Cited by 6

Transfer learning for activity recognition via sensor mapping

Hu, D. H., & Yang, Q. (2011) · Rare & Special e-Zone (The Hong Kong University of Science and Technology) · doi:10.5591/978-1-57735-516-8/ijcai11-328 · Cited by 65

Knowledge Transfer to Boost Human Activity Recognition Performance

Maučec, M. S., & Donaj, G. (2026) · IGI Global eBooks · doi:10.4018/979-8-3693-5638-8.ch019

Transfer Learning Enhanced Vision-based Human Activity Recognition: A Decade-long Analysis

Ray, A., Kolekar, M. H., Balasubramanian, R., & Hafiane, A. (2022) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2022.100142 · Cited by 103

Activity Recognition Using Transfer Learning

(2017) · Sensors and Materials · doi:10.18494/sam.2017.1546 · Cited by 24

Literature Review on Transfer Learning for Human Activity Recognition Using Mobile and Wearable Devices with Environmental Technology

Hernandez-Cruz, N., Lundström, J., Favela, J., McChesney, I., & Bert Arnrich, A. (2020) · SN Computer Science · doi:10.1007/s42979-020-0070-4 · Cited by 60