Transfer Learning for Visual Categorization: A Survey

Distinctive Image Features from Scale-Invariant Keypoints

Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589

Histograms of Oriented Gradients for Human Detection

Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584

The Elements of Statistical Learning

Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162

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

Principal component analysis

Wold, S., Esbensen, K. H., & Geladi, P. L. M. (1987) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/0169-7439(87)80084-9 · Cited by 11,792

Recognition-by-components: A theory of human image understanding.

Biederman, I. (1987) · Psychological Review · doi:10.1037/0033-295x.94.2.115 · Cited by 5,621

Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries

Elad, M., & Aharon, M. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.881969 · Cited by 5,321

Hmdb: a large video database for human motion recognition

Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., & Serre, T. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126543 · Cited by 3,965

Learning realistic human actions from movies

Ivan Laptev, A., Marszałek, M., Schmid, C., & Rozenfeld, B. (2008) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2008.4587756 · Cited by 3,481

FA‐YOLO: An Improved YOLO Model for Infrared Occlusion Object Detection under Confusing Background

Du, S., Zhang, B., Zhang, P., Xiang, P., & Xue, H. Y. (2021) · Wireless Communications and Mobile Computing · doi:10.1155/2021/1896029 · Cited by 43

Weed recognition using deep learning techniques on class-imbalanced imagery

Hasan, A. S. M. M., Sohel, F. A., Diepeveen, D., Laga, H., & Jones, M. G. K. (2022) · Australian Journal of Agricultural Research · doi:10.1071/cp21626 · Cited by 46

Deep Convolutional Neural Network (Falcon) and transfer learning‐based approach to detect malarial parasite

Banerjee, T., Jain, A., Sethuraman, S. C., Satapathy, S. C., Karthikeyan, S., & Jubilson, E. A. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-10946-5 · Cited by 42

A deep learning approach for Maize Lethal Necrosis and Maize Streak Virus disease detection

O’Halloran, T., Obaido, G., Otegbade, B., & Mienye, I. D. (2024) · Machine Learning with Applications · doi:10.1016/j.mlwa.2024.100556 · Cited by 44

Domain class consistency based transfer learning for image classification across domains

Zhang, L., Yang, J. J., & Zhang, D. D. (2017) · Information Sciences · doi:10.1016/j.ins.2017.08.034 · Cited by 42

Heterogeneous Multitask Metric Learning Across Multiple Domains

Luo, Y., Wen, Y., & Tao, D. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2750321 · Cited by 41

Cycle-Consistent Domain Adaptive Faster RCNN

Zhang, D., Li, J., Xiong, L., Lin, L., Ye, M., & Yang, S. (2019) · IEEE Access · doi:10.1109/access.2019.2938837 · Cited by 45

Multisource Heterogeneous Domain Adaptation With Conditional Weighting Adversarial Network

Yao, Y., Li, X., Zhang, Y., & Ye, Y. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3105868 · Cited by 44

Deep Representation Learning: Fundamentals, Technologies, Applications, and Open Challenges

Payandeh, A., Baghaei, K. T., Fayyazsanavi, P., Ramezani, S. B., Chen, Z., & Rahimi, S. (2023) · IEEE Access · doi:10.1109/access.2023.3335196 · Cited by 49

A framework for semi-supervised metric transfer learning on manifolds

Sanodiya, R. K., & Mathew, J. (2019) · Knowledge-Based Systems · doi:10.1016/j.knosys.2019.03.021 · Cited by 40

Manifold Transfer Learning via Discriminant Regression Analysis

Lu, Y., Wang, W., Yuan, C., Li, X., & Lai, Z. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.3007340 · Cited by 40

Transductive Relation-Propagation With Decoupling Training for Few-Shot Learning

Ma, Y., Bai, S., Liu, W., Wang, S., Yu, Y., Bai, X. P., Liu, X., & Wang, M. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3082928 · Cited by 41

A method for predicting hobbing tool wear based on CNC real-time monitoring data and deep learning

Wang, D., Hong, R., & Lin, X. (2021) · Precision Engineering · doi:10.1016/j.precisioneng.2021.08.010 · Cited by 40

Aligning Correlation Information for Domain Adaptation in Action Recognition

Xu, Y., Cao, H., Mao, K., Chen, Z., Xie, L., & Yang, J. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3212909 · Cited by 46

A novel active multi-source transfer learning algorithm for time series forecasting

Gu, Q., & Dai, Q. (2020) · Applied Intelligence · doi:10.1007/s10489-020-01871-5 · Cited by 39

FOOD-IMAGE CLASSIFICATION USING NEURAL NETWORK MODEL

Goh, A. M., & Yann, X. L. (2021) · International Journal of Electronics Engineering and Applications · doi:10.30696/ijeea.ix.iii.2021.12-22 · Cited by 38

Posture Recognition Using Ensemble Deep Models under Various Home Environments

Byeon, Y.-H., Lee, J., Kim, D., & Kwak, K.-C. (2020) · Applied Sciences · doi:10.3390/app10041287 · Cited by 38

On Physical-Layer Authentication via Online Transfer Learning

Chen, Y., Ho, P., Wen, H., Chang, S. Y., & Real, S. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3086581 · Cited by 37

Dual feature extraction based convolutional neural network classifier for magnetic resonance imaging tumor detection using U-Net and three-dimensional convolutional neural network

Kumar, R. S., Nagaraj, B., Manimegalai, P., & Ajay, P. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108010 · Cited by 37

Arousal Recognition Using Audio-Visual Features and FMRI-Based Brain Response

Han, J., Ji, X., Hu, X., Guo, L., & Liu, T. (2015) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2015.2411280 · Cited by 37

PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-Modalities

Wang, L., Gao, C., Yang, L., Zhao, Y., Zuo, W., & Meng, D. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01231-1_24 · Cited by 37

Deep conditional adaptation networks and label correlation transfer for unsupervised domain adaptation

Chen, Y., Yang, C., Zhang, Y., & Li, Y. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.107072 · Cited by 37

Subjective and objective quality assessment for image restoration: A critical survey

Hu, B., Li, L., Wu, J., & Qian, J. (2020) · Signal Processing Image Communication · doi:10.1016/j.image.2020.115839 · Cited by 37

A Comparative Analysis of Deep Learning Models for Automated Cross-Preparation Diagnosis of Multi-Cell Liquid Pap Smear Images

Benyes, Y. K., Welch, E. C., Singhal, A., Ou, J. J., & Tripathi, A. (2022) · Diagnostics · doi:10.3390/diagnostics12081838 · Cited by 37

Transfer learning and its extensive appositeness in human activity recognition: A survey

Ray, A., & Kolekar, M. H. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122538 · Cited by 36

Transfer learning for end-product quality prediction of batch processes using domain-adaption joint-Y PLS

Jia, R., Zhang, S., & You, F. (2020) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2020.106943 · Cited by 36

Transfer Learning for Renewable Energy Systems: A Survey

Al-Hajj, R., Assi, A., Neji, B., Ghandour, R., & Barakeh, Z. A. (2023) · Sustainability · doi:10.3390/su15119131 · Cited by 35

Learning salient visual word for scalable mobile image retrieval

Yang, X., Qian, X., & Mei, T. (2015) · Pattern Recognition · doi:10.1016/j.patcog.2014.12.017 · Cited by 35

AI Inspired Intelligent Resource Management in Future Wireless Network

Fu, S., Yang, F., & Xiao, Y. (2020) · IEEE Access · doi:10.1109/access.2020.2968554 · Cited by 35

Deep visual unsupervised domain adaptation for classification tasks: a survey

Madadi, Y., Seydi, V., Nasrollahi, K., Hosseini, R., & Moeslund, T. (2020) · IET Image Processing · doi:10.1049/iet-ipr.2020.0087 · Cited by 36

A Transfer Learning Framework for Predictive Energy-Related Scenarios in Smart Buildings

González-Vidal, A., Mendoza-Bernal, J., Niu, S., Skármeta, A., & Song, H. (2022) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2022.3179222 · Cited by 35

Weighted Correlation Embedding Learning for Domain Adaptation

Lu, Y., Zhu, Q., Zhang, B., Lai, Z., & Li, X. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3193758 · Cited by 35

Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift

Ott, F., Rügamer, D., Heublein, L., Bischl, B., & Mutschler, C. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548167 · Cited by 42

Enhanced Knowledge-Leverage-Based TSK Fuzzy System Modeling for Inductive Transfer Learning

Deng, Z., Jiang, Y., Ishibuchi, H., Choi, K., & Wang, S. (2016) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2903725 · Cited by 35

Automatic Facial Recognition of Williams-Beuren Syndrome Based on Deep Convolutional Neural Networks

Liu, H., Mo, Z., Yang, H., Zhang, Z., Hong, D., Wen, L., Lin, M.-Y., Zheng, Y.-Y., Zhang, Z., Xu, X., et al. (2021) · Frontiers in Pediatrics · doi:10.3389/fped.2021.648255 · Cited by 34

Progressive low-rank subspace alignment based on semi-supervised joint domain adaption for personalized emotion recognition

Luo, J., Wu, M., Wang, Z., Chen, Y., & Yang, Y. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.05.064 · Cited by 34

A white-box analysis on the writer-independent dichotomy transformation applied to offline handwritten signature verification

Souza, V. L. F., Oliveira, A. L. I., Cruz, R. M. O., & Sabourin, R. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113397 · Cited by 34

Brain tumor classification using ResNet50-convolutional block attention module

Oladimeji, O. O., & Ibitoye, A. (2023) · Applied Computing and Informatics · doi:10.1108/aci-09-2023-0022 · Cited by 41

Knowing Your Dog Breed: Identifying a Dog Breed with Deep Learning

Borwarnginn, P., Kusakunniran, W., Karnjanapreechakorn, S., & Thongkanchorn, K. (2020) · Machine Intelligence Research · doi:10.1007/s11633-020-1261-0 · Cited by 34

Predictive Analysis of Diabetic Retinopathy with Transfer Learning

Salvi, R. S., Labhsetwar, S. R., Kolte, P. A., Venkatesh, V. S., & Baretto, A. M. (2021) · Biennial International Conference on Nascent Technologies in Engineering (ICNTE) · doi:10.1109/icnte51185.2021.9487789 · Cited by 33

Deep Transfer Learning Enables Robust Prediction of Antimicrobial Resistance for Novel Antibiotics

Ren, Y., Chakraborty, T., Doijad, S. P., Falgenhauer, L., Falgenhauer, J. C., Goesmann, A., Schwengers, O., & Heider, D. (2022) · Antibiotics · doi:10.3390/antibiotics11111611 · Cited by 33

Influence of AVC and HEVC Compression on Detection of Vehicles Through Faster R-CNN

Chan, P. H., Huggett, A., Souvalioti, G., Jennings, P., & Donzella, V. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3308344 · Cited by 33

MultiTL-KELM: A multi-task learning algorithm for multi-step-ahead time series prediction

Ye, R., & Dai, Q. (2019) · Applied Soft Computing · doi:10.1016/j.asoc.2019.03.039 · Cited by 32

Dynamic Double Classifiers Approximation for Cross-Domain Recognition

Fang, X., Han, N., Zhou, G., Teng, S., Xu, Y. D., & Xie, S. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.3004398 · Cited by 32

Workpiece image-based tool wear classification in blanking processes using deep convolutional neural networks

Molitor, D. A., Kubik, C., Hetfleisch, R. H., & Groche, P. (2022) · Production Engineering · doi:10.1007/s11740-022-01113-2 · Cited by 32

Unsupervised sleep staging system based on domain adaptation

Zhao, R., Xia, Y., & Zhang, Y. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102937 · Cited by 31

Deep weighted joint distribution adaption network for fault diagnosis of blast furnace ironmaking process

Gao, D., Zhu, X., Yang, C., Huang, X., & Wang, W. (2022) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2022.107797 · Cited by 31

Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer

Ge, Z., Shang, F., Liu, H., Liu, Y., Wan, L., Feng, W., & Wang, X. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612070 · Cited by 35

MWIRGas-YOLO: Gas Leakage Detection Based on Mid-Wave Infrared Imaging

Xu, S., Wang, X., Sun, Q., & Dong, K. (2024) · Sensors · doi:10.3390/s24134345 · Cited by 33

Novel roughness measurement for grinding surfaces using simulated data by transfer kernel learning

Zhang, H., Liu, J., Chen, S., & Wang, W. (2018) · Applied Soft Computing · doi:10.1016/j.asoc.2018.08.042 · Cited by 30

A layered working condition perception integrating handcrafted with deep features for froth flotation

Gao, X., Tang, Z., Xie, Y., Zhang, H., & Gui, W. (2021) · Minerals Engineering · doi:10.1016/j.mineng.2021.107059 · Cited by 30

An Adaptive Focal Loss Function Based on Transfer Learning for Few-Shot Radar Signal Intra-Pulse Modulation Classification

Jing, Z., Li, P., Wu, B., Yuan, S., & Chen, Y. (2022) · Remote Sensing · doi:10.3390/rs14081950 · Cited by 30

MMFSL: A Novel Multimodal Few-Shot Learning Framework for Fault Diagnosis of Industrial Bearings

Cheng, L., An, Z., Guo, Y., Ren, M., Yang, Z., & McLoone, S. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3289549 · Cited by 30

A comparative study of image classification algorithms for Foraminifera identification

Zhong, B., Ge, Q., Kanakiya, B., Marchitto, R. M. T., & Lobaton, E. J. (2017) · IEEE Symposium Series on Computational Intelligence (SSCI) · doi:10.1109/ssci.2017.8285164 · Cited by 30

A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks

Perera, R., & Agrawal, V. (2023) · Mechanics of Materials · doi:10.1016/j.mechmat.2023.104639 · Cited by 29

Discriminative Semantic Subspace Analysis for Relevance Feedback

Zhang, L., Shum, H. P. H., & Shao, L. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2516947 · Cited by 29

Image-Based Incipient Fault Classification of Electrical Substation Equipment by Transfer Learning of Deep Convolutional Neural Network

Guan, X., Gao, W., Peng, H., Shu, N., & Gao, W. (2021) · Canadian Journal of Electrical and Computer Engineering · doi:10.1109/icjece.2021.3109293 · Cited by 29

A New Hope in the Fight Against Antimicrobial Resistance with Artificial Intelligence

Tran, M., Nguyen, N. Q., & Pham, H. T. (2022) · Infection and Drug Resistance · doi:10.2147/idr.s362356 · Cited by 29

Unknown, Atypical and Polymorphic Network Intrusion Detection: A Systematic Survey

Sabeel, U., Heydari, S. S., El‐Khatib, K., & Elgazzar, K. (2023) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2023.3298533 · Cited by 29

Prediction of sludge bulking using the knowledge-leverage-based fuzzy neural network

Han, H., Liu, Z., Ge, L., & Qiao, J. (2017) · Water Science & Technology · doi:10.2166/wst.2017.574 · Cited by 29

A survey of deep learning algorithms for colorectal polyp segmentation

Li, S., Ren, Y., Yu, Y., Jiang, Q., He, X., & Li, H. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128767 · Cited by 28

Artificial intelligence in molecular imaging

Herskovits, E. H. (2021) · Annals of Translational Medicine · doi:10.21037/atm-20-6191 · Cited by 29

Human–Robot Collaboration Using Sequential-Recurrent-Convolution-Network-Based Dynamic Face Emotion and Wireless Speech Command Recognitions

Hwang, C., Deng, Y., & Pu, S. (2022) · IEEE Access · doi:10.1109/access.2022.3228825 · Cited by 28

Local structure preserving discriminative projections for RGB-D sensor-based scene classification

Tao, D., Cheng, J. S., Xu, L. H., & Jiang, Y. (2015) · Information Sciences · doi:10.1016/j.ins.2015.03.031 · Cited by 27

On Security Threats of Botnets to Cyber Systems

Lange, T., & Kettani, H. (2019) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin.2019.8711780 · Cited by 27

Latent Elastic-Net Transfer Learning

Han, N., Wu, J., Fang, X., Xie, S., Zhan, S., Xie, K., & Li, X. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2952739 · Cited by 27

Office Garbage Intelligent Classification Based on Inception-v3 Transfer Learning Model

Feng, J., & Tang, X. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1487/1/012008 · Cited by 27

Transfer Learning Approach for the Classification of Conidial Fungi (Genus Aspergillus) Thru Pre-trained Deep Learning Models

Mital, M. E. G., Tobias, R. R., Villaruel, H. V., Maningo, J. M. Z., Billones, R. K. C., Vicerra, R. R. P., Bandala, A. A., & Dadios, E. P. (2020) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon50793.2020.9293803 · Cited by 27

Transfer Learning Algorithm With Knowledge Division Level

Han, H., Liu, H., Yang, C., & Qiao, J. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3151646 · Cited by 27

Human-inspired spatiotemporal feature extraction and fusion network for weather forecasting

Wu, H., Liang, Y., & Zuo, J. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118089 · Cited by 27

Multi-source deep transfer learning for cross-sensor biometrics

Kandaswamy, C., Monteiro, J. C., Silva, L. M., & Cardoso, J. S. (2016) · Neural Computing and Applications · doi:10.1007/s00521-016-2325-5 · Cited by 27

3-D Laser-Based Multiclass and Multiview Object Detection in Cluttered Indoor Scenes

Zhang, X., Zhuang, Y., Hu, H., & Wang, W. (2015) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2015.2496195 · Cited by 27

Equity in Unsupervised Domain Adaptation by Nuclear Norm Maximization

Wang, M., Wang, S., Yang, X., Yuan, J., & Zhang, W. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3346444 · Cited by 26

Development Of A Vision- based Anti-drone Identification Friend Or Foe Model To Recognize Birds And Drones Using Deep Learning

Yasmine, G., Gmira, M., & Medromi, H. (2024) · Applied Artificial Intelligence · doi:10.1080/08839514.2024.2318672 · Cited by 26

Binary decisions of artificial intelligence to classify third molar development around the legal age thresholds of 14, 16 and 18 years

Franco, A., Murray, J., Heng, D., Lygate, A., Moreira, D., Ferreira, J., Paulo, D. M. E., Machado, C. E. P., Bueno, J. M., Mânica, S., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-55497-5 · Cited by 27

Exploring Correlations Among Tasks, Clusters, and Features for Multitask Clustering

Cao, W., Wu, S., Yu, Z., & Wong, H. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2839114 · Cited by 26

Hybrid Hierarchical Reinforcement Learning for online guidance and navigation with partial observability

Zhou, Y., Kampen, E.-J. V., & Chu, Q. P. (2018) · Neurocomputing · doi:10.1016/j.neucom.2018.11.072 · Cited by 26

Semisupervised Discriminant Multimanifold Analysis for Action Recognition

Xu, Z., Hu, R., Chen, J., Chen, C., Jiang, J., Li, J., & Li, H. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2886008 · Cited by 26

Bringing Semantics to the Vineyard: An Approach on Deep Learning-Based Vine Trunk Detection

Aguiar, A., Monteiro, N. N., dos Santos, F. N., Pires, E. J. S., da Silva, D. Q., Sousa, A. J., & Boaventura‐Cunha, J. (2021) · Agriculture · doi:10.3390/agriculture11020131 · Cited by 26

Comparison of Four Transfer Learning and Hybrid CNN Models on Three Types of Lung Cancer

Sultana, A., Khan, T. T., & Hossain, T. (2021) · International Conference on Electrical Information and Communication Technology (EICT) · doi:10.1109/eict54103.2021.9733614 · Cited by 26

Henry gas bird swarm optimization algorithm‐based deep learning for brain tumor classification using magnetic resonance imaging

Omana, S. P., Dar, J. A., Kumar, T. R., Sampath, A. K., & Sharma, S. K. (2022) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.7541 · Cited by 26

Circular systems engineering

Dávid, I., Bork, D., & Kappel, G. (2024) · Software & Systems Modeling · doi:10.1007/s10270-024-01154-4 · Cited by 28

Beyond Weakly Supervised: Pseudo Ground Truths Mining for Missing Bounding-Boxes Object Detection

Zhang, Y., Ding, M., Bai, Y., Xu, M., & Ghanem, B. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2898559 · Cited by 26

Classifying Barako coffee leaf diseases using deep convolutional models

Montalbo, F. J. P., & Hernandez, A. A. (2020) · International Journal of Advances in Intelligent Informatics · doi:10.26555/ijain.v6i2.495 · Cited by 30

Improvement of Heterogeneous Transfer Learning Efficiency by Using Hebbian Learning Principle

Magotra, A., & Kim, J. (2020) · Applied Sciences · doi:10.3390/app10165631 · Cited by 27

Conditional Generative Adversarial Networks and Deep Learning Data Augmentation: A Multi-Perspective Data-Driven Survey Across Multiple Application Fields and Classification Architectures

Ribas, L. C., Casaca, W. C. D. O., & Fares, R. T. (2025) · AI · doi:10.3390/ai6020032 · Cited by 25

SVM-CNN-Based Fusion Algorithm for Vehicle Navigation Considering Atypical Observations

Sun, J., Wu, Z., Yin, Z., & Yang, Z. (2018) · IEEE Signal Processing Letters · doi:10.1109/lsp.2018.2885511 · Cited by 25

Adaptation-Oriented Feature Projection for One-shot Action Recognition

Zou, Y., Shi, Y., Shi, D., Wang, Y., Liang, Y., & Tian, Y. (2020) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2020.2972128 · Cited by 25

Transferable Feature Selection for Unsupervised Domain Adaptation

Yan, Y., Wu, H., Ye, Y., Bi, C., Lu, M., Liu, D., Wu, Q., & Ng, M. K. (2021) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2021.3060037 · Cited by 25

State of health forecasting of Lithium-ion batteries applicable in real-world operational conditions

von Bülow, F., Mentz, J., & Meisen, T. (2021) · Journal of Energy Storage · doi:10.1016/j.est.2021.103439 · Cited by 25

Forecasting of short term electric power consumption for different types buildings using improved transfer learning: A case study of primary school in China

Zhou, M., Yu, J., Sun, F., & Wang, M. (2023) · Journal of Building Engineering · doi:10.1016/j.jobe.2023.107618 · Cited by 25

An Artificial Intelligence System (Ai-Doctor) for the Whole Diagnostic and Treatment Process of Ischaemic Retinal Diseases : A Multi-Tasks Modelling Study

Zhao, X., Lin, Z., Yu, S., Xiao, J., Xie, L., Xu, Y., Tsui, C., Cui, K., Zhao, L., Zhang, G., et al. (2022) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101197 · Cited by 25

Federated Multimodal Learning for Privacy-Preserving Driver Break Recommendations in Consumer Electronics

Liu, P., Jiang, L., Lin, H., Hu, J. W., Garg, S., & Alrashoud, M. R. (2023) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2023.3339630 · Cited by 25

Toward a Deep Smart Waste Management System based on Pattern Recognition and Transfer learning

Jadli, A., & Hain, M. (2020) · International Conference on Advanced Communication Technologies and Networking (CommNet) · doi:10.1109/commnet49926.2020.9199615 · Cited by 27

Transferability-Guided Cross-Domain Cross-Task Transfer Learning

Tan, Y., Zhang, E., Li, Y., Huang, S.-L., & Zhang, X.-P. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3358094 · Cited by 24

Geometry Regularized Joint Dictionary Learning for Cross-Modality Image Synthesis in Magnetic Resonance Imaging

Huang, Y., Beltrachini, L., Shao, L., & Frangi, A. F. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46630-9_12 · Cited by 24

Deep Transfer Learning for Cross-subject and Cross-experiment Prediction of Image Rapid Serial Visual Presentation Events from EEG Data

Hajinoroozi, M., Mao, Z., Lin, Y., & Huang, Y. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58628-1_4 · Cited by 24

A multi-task transfer learning method with dictionary learning

Zheng, X. W., Lin, L., Liu, B., Xiao, Y., & Xiong, X. (2019) · Knowledge-Based Systems · doi:10.1016/j.knosys.2019.105233 · Cited by 24

A Deep Learning Model for Screening Multiple Abnormal Findings in Ophthalmic Ultrasonography (With Video)

Chen, D., Yu, Y., Zhou, Y., Peng, B., Wang, Y., Hu, S., Tian, M., Wan, S., Gao, Y., Wang, Y., et al. (2021) · Translational Vision Science & Technology · doi:10.1167/tvst.10.4.22 · Cited by 24

Learning Smooth Representation for Unsupervised Domain Adaptation

Cai, G., He, L., Zhou, M., Alhumade, H., & Hu, D. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3119889 · Cited by 25

Transfer learning for visual recognition and text categorization

Duan, L. (2012) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/48658

Transfer Learning for Cross-Dataset Recognition: A SurveyPreprint

Zhang, J., Li, W., & Ogunbona, P. (2017) · arXiv (Cornell University) · Cited by 31

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

Boosted Cross-Domain Dictionary Learning for Visual Categorization

Zhu, F., Shao, L., & Fang, Y. (2016) · IEEE Intelligent Systems · doi:10.1109/mis.2016.30 · Cited by 6

Visual Feature Learning

Zhu, F. (2015) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · Cited by 1