Incremental supervised learning: Algorithms and applications in pattern recognition

Incremental and Decremental Support Vector Machine Learning

Cauwenberghs, G., & Poggio, T. (2000) · Cited by 1,156 · see citing works

Learn++: an incremental learning algorithm for supervised neural networks

Polikar, R., Upda, L., Upda, S. S., & Honavar, V. (2001) · IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/5326.983933 · Cited by 888 · see citing works

Incremental Induction of Decision Trees

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Incremental learning with support vector machines

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TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic‐scale variations for the period 2002–2003

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A case study of incremental concept induction

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Handling concept drifts in incremental learning with support vector machines

Syed, N. A., Liu, H., & Sung, K. K. (1999) · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/312129.312267 · Cited by 281 · see citing works

Svm incremental learning, adaptation and optimization

Diehl, C., & Cauwenberghs, G. (2004) · doi:10.1109/ijcnn.2003.1223991 · Cited by 263 · see citing works

A novel incremental principal component analysis and its application for face recognition

Zhao, H., Yuen, P. C., & Kwok, J. T.-Y. (2006) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2006.870645 · Cited by 223 · see citing works

Incremental Support Vector Machine Classification

Fung, G., & Mangasarian, O. L. (2002) · SIAM International Conference on Data Mining · doi:10.1137/1.9781611972726.15 · Cited by 145 · see citing works

Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing

Sarwar, S. S., Ankit, A., & Roy, K. (2019) · IEEE Access · doi:10.1109/access.2019.2963056 · Cited by 127 · see citing works

Incremental Learning of Chunk Data for Online Pattern Classification Systems

Ozawa, S., Pang, S., & Kasabov, N. K. (2008) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2007.2000059 · Cited by 118 · see citing works

Incremental learning of feature space and classifier for face recognition

Ozawa, S., Toh, S. L., Abe, S., Pang, S., & Kasabov, N. K. (2005) · Neural Networks · doi:10.1016/j.neunet.2005.06.016 · Cited by 107 · see citing works

Incremental Support Vector Machine Learning: A Local Approach

Ralaivola, L., & d’Alché–Buc, F. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44668-0_46 · Cited by 105 · see citing works

Incremental action recognition using feature-tree

Reddy, K. K., Liu, J., & Shah, M. A. (2009) · IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2009.5459374 · Cited by 101 · see citing works

Interannual variations in continental‐scale net carbon exchange and sensitivity to observing networks estimated from atmospheric CO2 inversions for the period 1980 to 2005

Gurney, K. R., Baker, D. F., Rayner, P. J., & Denning, S. (2008) · Global Biogeochemical Cycles · doi:10.1029/2007gb003082 · Cited by 99 · see citing works

Incremental learning for place recognition in dynamic environments

Luo, J., Pronobis, A., Barbara Caputo, B., & Jensfelt, P. (2007) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2007.4398986 · Cited by 89 · see citing works

Incremental Learning: Areas and Methods – A Survey

Joshi, P. (2012) · International Journal of Data Mining & Knowledge Management Process · doi:10.5121/ijdkp.2012.2504 · Cited by 69 · see citing works

Application of an incremental SVM algorithm for on-line human recognition from video surveillance using texture and color features

Lu, Y., Boukharouba, K., Boonært, J., Fleury, A., & Lecœuche, S. (2013) · Neurocomputing · doi:10.1016/j.neucom.2012.08.071 · Cited by 63 · see citing works

Incremental Learning of Boosted Face Detector

Huang, C., Ai, H., Yamashita, T., Lao, S., & Kawade, M. (2007) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2007.4408850 · Cited by 43 · see citing works

Ensemble of SVMs for Incremental Learning

Erdem, Z., Robi Polikar, A., Gürgen, F. S., & Yumuşak, N. (2005) · Lecture notes in computer science · doi:10.1007/11494683_25 · Cited by 43 · see citing works

Incremental Learning with SVM for Multimodal Classification of Prostatic Adenocarcinoma

Molina, J. F. G., Zheng, L., Sertdemir, M., Dinter, D. J., Schönberg, S. O., & Rädle, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0093600 · Cited by 42 · see citing works

Incremental class learning approach and its application to handwritten digit recognition

Mańdziuk, J., & Shastri, L. (2002) · Information Sciences · doi:10.1016/s0020-0255(02)00170-6 · Cited by 28 · see citing works

A Face Recognition System Using Neural Networks with Incremental Learning Ability

Toh, S. L., & Ozawa, S. (2003) · Cited by 16 · see citing works

Adaptive SVM for Data Stream Classification

Lawal, I. A., & Abdulkarim, S. A. (2017) · South African Computer Journal · doi:10.18489/sacj.v29i1.414 · Cited by 15 · see citing works

Evaluating SPAN Incremental Learning for Handwritten Digit Recognition

Mohemmed, A. W., Lu, G., & Kasabov, N. K. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-34487-9_81 · Cited by 11 · see citing works

An incremental structured part model for object recognition

Bai, X. P., Ren, P., Zhang, H., & Zhou, J. W. (2014) · Neurocomputing · doi:10.1016/j.neucom.2014.12.004 · Cited by 10 · see citing works

A Face Recognition System using Neural Networks with Incremental Learning Ability

Ghassabeh, Y. A., & Moghaddam, H. A. (2007) · IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA) · doi:10.1109/cira.2007.382904 · Cited by 10 · see citing works

Incremental Learning Framework for Indoor Scene Recognition

Kawewong, A., Pimup, R., & Hasegawa, O. (2013) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v27i1.8584 · Cited by 10 · see citing works

Decremental Learning of Evolving Fuzzy Inference Systems: Application to Handwritten Gesture Recognition

Bouillon, M., Anquetil, É., & Almaksour, A. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39712-7_9 · Cited by 8 · see citing works

The Neural Networks with an Incremental Learning Algorithm Approach for Mass Classification in Breast Cancer

Zribi, M., & Boujelbène, Y. (2016) · International Journal of Biomedical Data Mining · doi:10.4172/2090-4924.1000118 · Cited by 8 · see citing works

Budget restricted incremental learning with pre-trained convolutional neural networks and binary associative memories

Hacene, G. B., Gripon, V., Farrugia, N., Arzel, M., & Jézéquel, M. (2017) · SiPS ... design and implementation - IEEE Workshop on Signal Processing Systems · doi:10.1109/sips.2017.8109978 · Cited by 7 · see citing works

An incremental learning algorithm based on Support Vector Machine for pattern recognition

Zou, L., Zhang, T., & Cao, Z. (2009) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.832348 · Cited by 6 · see citing works

INCREMENTAL LEARNING WITH PRE-TRAINED CONVOLUTIONAL NEURAL NETWORKS AND BINARY ASSOCIATIVE MEMORIES

Hacene, G. B., Gripon, V., Farrugia, N., Arzel, M., & Jézéquel, M. (2017) · Cited by 1 · see citing works

Incremental Learning in Deep Neural Networks

Liu, Y. (2015) · Tampere University of Technology Institutional Repository · Cited by 1 · see citing works

A review and perspective on hybrid modeling methodologies

Schweidtmann, A. M., Zhang, D., & von Stosch, M. (2024) · Digital Chemical Engineering · doi:10.1016/j.dche.2023.100136 · Cited by 178 · see citing works

An Appraisal of Incremental Learning Methods

Luo, Y., Yin, L., Bai, W., & Mao, K. (2020) · Entropy · doi:10.3390/e22111190 · Cited by 120 · see citing works

An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes

Amin, A., Adnan, A., & Anwar, S. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.110103 · Cited by 83 · see citing works

Predictive process monitoring: concepts, challenges, and future research directions

Ceravolo, P., Comuzzi, M., Weerdt, J. D., Francescomarino, C. D., & Maggi, F. M. (2024) · Process Science · doi:10.1007/s44311-024-00002-4 · Cited by 58 · see citing works

Smart User Consumption Profiling: Incremental Learning-Based OTT Service Degradation

Rojas, J. S., Pekár, A., Gallón, Á. R., & Corrales, J. C. (2020) · IEEE Access · doi:10.1109/access.2020.3037971 · Cited by 36 · see citing works

A Taxonomy of Food Supply Chain Problems from a Computational Intelligence Perspective

Angarita-Zapata, J. S., Alonso‐Vicario, A., Masegosa, A. D., & Legarda, J. (2021) · Sensors · doi:10.3390/s21206910 · Cited by 35 · see citing works

A Bibliometric Analysis and Benchmark of Machine Learning and AutoML in Crash Severity Prediction: The Case Study of Three Colombian Cities

Angarita-Zapata, J. S., Maestre-Gongora, G. P., & Calderín, J. F. (2021) · Sensors · doi:10.3390/s21248401 · Cited by 30 · see citing works

Using Stream Data Processing for Real-Time Occupancy Detection in Smart Buildings

Elkhoukhi, H., Bakhouya, M., Ouadghiri, D. E., & Hanifi, M. (2022) · Sensors · doi:10.3390/s22062371 · Cited by 29 · see citing works

Prediction of corrosion fatigue crack growth rate in aluminum alloys based on incremental learning strategy

Peng, Y., Zhang, Y., Zhang, L., Yao, L., & Guo, X. (2024) · International Journal of Fatigue · doi:10.1016/j.ijfatigue.2024.108481 · Cited by 25 · see citing works

Integration of the Machine Learning Algorithms and I-MR Statistical Process Control for Solar Energy

Atalan, Y. A., & Atalan, A. (2023) · Sustainability · doi:10.3390/su151813782 · Cited by 20 · see citing works

3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning

van Eijnatten, M. A. J. M., Rundo, L., Batenburg, K. J., Lucka, F. F., Beddowes, E. J., Caldas, C., Gallagher, F. A., Sala, E., Schönlieb, C., & Woitek, R. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106261 · Cited by 18 · see citing works

An incremental learning approach to prediction models of SEIRD variables in the context of the COVID-19 pandemic

Camargo, E., Aguilar, J., Quintero, Y. M., Rivas, F., & Ardila, D. (2022) · Health and Technology · doi:10.1007/s12553-022-00668-5 · Cited by 17 · see citing works

CEDUP: Using incremental learning modeling to explore Spatio-temporal carbon emission distribution and unearthed patterns at the municipal level

Wú, Z., Qiao, R., Liu, X., Gao, S., Ao, X., He, Z., & Xia, L. (2023) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2023.106980 · Cited by 16 · see citing works

Application of Deep Learning and Machine Learning in Pattern Recognition

Raj, E. F. I., & Balaji, M. (2022) · Transactions on computer systems and networks · doi:10.1007/978-981-16-9324-3_4 · Cited by 15 · see citing works

Detecting and Fact-checking Misinformation using “Veracity Scanning Model”

Barve, Y., Saini, J. R., Kotecha, K. V., & Gaikwad, H. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.0130225 · Cited by 14 · see citing works

Towards open-world recognition: Critical problems and challenges

Wang, K., Li, Z., Yang, C., Dong, W., & Chen, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110042 · Cited by 12 · see citing works

Android Malware Classification: Updating Features Through Incremental Learning Approach(UFILA)

Sawadogo, Z., Mendy, G., Dembélé, J. M., & Ouya, S. (2022) · International Conference on Advanced Communication Technology · doi:10.23919/icact53585.2022.9728977 · Cited by 10 · see citing works

Towards a self-sufficient face verification system

López‐López, E., Regueiro, C. V., Pardo, X. M., Franco, A., & Lumini, A. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.114734 · Cited by 10 · see citing works

Elephant Flow Detection With Random Forest Models Under Programmable Network Dataplane Constraints

Jurkiewicz, P., Kądziołka, B., Kantor, M., Wójcik, R., & Domżał, J. (2024) · IEEE Access · doi:10.1109/access.2024.3485588 · Cited by 7 · see citing works

Incremental learning model for dynamical identification and classification of abnormal vibration in operational underground facilities

Chai, F., Zhou, B., Xie, X., Zhang, Z., & Wang, C. (2023) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2023.105251 · Cited by 7 · see citing works

Implementation of real-time incremental learning for ensemble hybrid model prediction in pilot scale bubble column aeration

Jul‐Rasmussen, P., Stevnsborg, M., Liang, X., & Huusom, J. K. (2024) · Digital Chemical Engineering · doi:10.1016/j.dche.2024.100212 · Cited by 7 · see citing works

A Novel Incremental Learning Algorithm Based on Incremental Vector Support Machina and Incremental Neural Network Learn++

Chefrour, A., Souici‐Meslati, L., Difi, I., & Bakkouche, N. (2019) · Revue d intelligence artificielle · doi:10.18280/ria.330303 · Cited by 7 · see citing works

Split incremental clustering algorithm of mixed data stream

Gorrab, S., Rejab, F. B., & Nouira, K. (2024) · Progress in Artificial Intelligence · doi:10.1007/s13748-024-00316-1 · Cited by 5 · see citing works

Research on Image Recognition based on Reinforcement Learning

Luo, J., & Luo, R. (2023) · International Conference on Computer Vision, Image and Deep Learning (CVIDL) · doi:10.1109/cvidl58838.2023.10166036 · Cited by 4 · see citing works

Investigating the Terrain of Class-Incremental Continual Learning: A Brief Survey

Nokhwal, S., Kumar, N., & Shiva, S. G. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-97-7426-5_25 · Cited by 4 · see citing works

Mining high influence co-location patterns from instances with attributes

Fang, D., Wang, L., Yang, P., & Chen, L. (2019) · Evolutionary Intelligence · doi:10.1007/s12065-019-00321-7 · Cited by 3 · see citing works

Expert-augmented Data-driven Safety Level Assessment Scheme with Incremental Learning

Liu, C., Zhang, Y., & He, X. Y. (2021) · CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS) · doi:10.1109/safeprocess52771.2021.9693634 · Cited by 3 · see citing works

Android Malware Detection: Feature Update Using Incremental Learning Approach: Further Investigation of UFILA

Sawadogo, Z., Dembélé, J. M., Mendy, G., & Ouya, S. (2023) · International Conference on Advanced Communication Technology · doi:10.23919/icact56868.2023.10079298 · Cited by 2 · see citing works

Advancing Telecom Customer Churn using Deep Learning

Seethalakshmi, R., & Varsha, B. S. (2024) · International Conference on Electronics, Communication and Aerospace Technology (ICECA) · doi:10.1109/iceca63461.2024.10801009 · Cited by 1 · see citing works

Automotive Cockpit-Driving Integration for Human-Centric Autonomous Driving: A Survey

Zhu, Z.-P., Zhao, S., Cai, M., Wang, C., & Du, A. (2025) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2025.3616947

Crypsis: an elitism-driven observer-based approach for detection and mitigation of concept drift, concept evolution, and label drift

Yanni, G. S., Rashad, H. S., & Maghraby, F. A. (2026) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-026-01191-1 · Cited by 1 · see citing works

DFT: A deep feature‐based semi‐supervised collaborative training for vehicle recognition in smart cities

Zhang, Y., Liu, Y., Yang, G.-M., & Song, J. (2021) · Expert Syst. J. Knowl. Eng. · doi:10.1111/exsy.12916 · Cited by 1 · see citing works

DP-GAN: A Novel Generative Adversarial Network-Based Drone Pilot Identification Scheme

Han, L., Liu, J., & Zhang, Y. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3331321 · Cited by 1 · see citing works

Enhancing handwritten numeric string recognition through incremental support vector machines

Putri, R. K., & Athoillah, M. (2024) · Journal of AppliedMath · doi:10.59400/jam.v2i1.373 · Cited by 1 · see citing works

Anonymous Spreaders Detection of False Information using Incremental Learning Approach

Barve, Y., & Saini, J. R. (2023) · International Conference on Communication and Electronics Systems (ICCES) · doi:10.1109/icces57224.2023.10192847 · Cited by 1 · see citing works

A Review of Cockpit-driving Integration for Human-centric Autonomous DrivingPreprint

Zhu, Z., Zhao, S., Wang, C., & Du, A. (2023) · doi:10.36227/techrxiv.24428014.v1 · Cited by 1 · see citing works

A Review of Cockpit-driving Integration for Human-centric Autonomous DrivingPreprint

Zhu, Z., Zhao, S., Wang, C., & Du, A. (2023) · doi:10.36227/techrxiv.24428014 · Cited by 1 · see citing works

Aprendizado Incremental de Redes RBF via Agrupamento Evolutivo de Fluxos de Dados

Menegaldi, T. M. D. L., Coelho, R. A., & de Castro, C. L. (2021) · Congresso Brasileiro de Inteligência Computacional (CBIC) · doi:10.21528/cbic2021-57

Outsmarting Spam: Resilient Model for Concept Drift and Evolving Threats

Yanni, G. S., Salah, H., & Maghraby, F. A. (2024) · International Conference on Computer Theory and Applications (ICCTA) · doi:10.1109/iccta64612.2024.10974776

Hybrid modeling framework for bioprocesses with minimal qualitative knowledge and scarce data

Martínez, C. A., Calvette, F. R., Péré, M., Barrientos, M. A., & Ossandón, S. (2026) · Applied Mathematical Modelling · doi:10.1101/2025.11.14.688550

SlidingGLCMK-NN Classifier for Stream Learning.

Alex, S. A., Estrela, V. V., Vaz, G. C., Iano, Y., de Oliveira, G. G., & Alves, Â. M. (2025) · International Conference on Big Data and Internet of Things (BDIOT) · doi:10.1145/3779153.3779162

Survey of incremental learning

Yang, Q., Gu, Y., & Wu, D. (2019) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2019.8832774 · Cited by 41 · see citing works

A Novel Incremental Learning Algorithm Based on Incremental Vector Support Machina and Incremental Neural Network Learn++

Chefrour, A., Souici‐Meslati, L., Difi, I., & Bakkouche, N. (2019) · Revue d intelligence artificielle · doi:10.18280/ria.330303 · Cited by 7 · see citing works

Adaptive Incremental Learning with an Ensemble of Support Vector Machines

Kapp, M. N., Sabourin, R., & Maupin, P. (2010) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2010.984 · Cited by 11 · see citing works

Methods for Incremental Learning : A Survey

Ade, R. R., & R, D. P. (2013) · International Journal of Data Mining & Knowledge Management Process · doi:10.5121/ijdkp.2013.3408 · Cited by 82 · see citing works

Incremental backpropagation learning networks

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