The Hierarchical Hidden Markov Model: Analysis and Applications

Maximum Likelihood from Incomplete Data Via the EM Algorithm

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Application of a new probabilistic model for recognizing complex patterns in glycans

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Customer Behaviour Hidden Markov Model

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Adaptive undersampling and short clip-based two-stream CNN-LSTM model for surgical phase recognition on cholecystectomy videos

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Variational Bayesian State Space Model for dynamic process fault detection

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Cross-entropic learning of a machine for the decision in a partially observable universe

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Sports Event Recognition Using Layered HMMS

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Dynamic hand gesture recognition using hierarchical dynamic Bayesian networks through low-level image processing

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LEARNING MUSICAL PITCH STRUCTURES WITH HIERARCHICAL HIDDEN MARKOV MODELS

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Asymmetric hidden Markov models

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Memory compression and thermal efficiency of quantum implementations of nondeterministic hidden Markov models

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A learning architecture for automating the intelligent environment

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A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology

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A Belief Networks-Based Generative Model for Structured Documents. An Application to the XML Categorization

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Motion-sound Mapping By Demonstration

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A unified approach to the recognition of complex actions from sequences of zone-crossings

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HIERARCHICAL CLASSIFICATION TREE MODELING OF NONSTATIONARY NOISE FOR ROBUST SPEECH RECOGNITION

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Stock Trading by Modelling Price Trend with Dynamic Bayesian Networks

Jangmin, O., Lee, J. W., Park, S.-B., & Zhang, B. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-28651-6_118 · Cited by 15

Hierarchical multi-channel hidden semi Markov graphical models for activity recognition

Natarajan, P., & Nevatia, R. (2012) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2012.08.011 · Cited by 15

Hidden Markov models in bearing fault diagnosis and prognosis

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Practical use of non-local features for statistical spoken language understanding

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Ambient Activity Recognition in Smart Environments for Cognitive Assistance

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Temporal segmentation and keyframe selection methods for user-generated video search-based annotation

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Polymorphic Malware Detection Using Hierarchical Hidden Markov Model

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Product named entity recognition in Chinese text

Zhao, J., & Liu, F. (2008) · Computers and the Humanities · doi:10.1007/s10579-008-9066-8 · Cited by 15

Segmentation of gait sequences using inertial sensor data in hereditary spastic paraplegia

Martindale, C. F., Strauss, M., Gaßner, H., List, J., Müller, M., Klucken, J., Kohl, Z., & Eskofier, B. M. (2017) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2017.8037062 · Cited by 15

Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models

Martindale, C. F., Hoenig, F., Strohrmann, C., & Eskofier, B. M. (2017) · Sensors · doi:10.3390/s17102328 · Cited by 15

A novel approach for data-driven process and condition monitoring systems on the example of mill-turn centers

Kißkalt, D., Fleischmann, H., Kreitlein, S., Knott, M., & Franke, J. E. (2018) · Production Engineering · doi:10.1007/s11740-018-0797-0 · Cited by 15

Functional Specification of Probabilistic Process Models ∗

Pfeffer, A. (2008) · Cited by 15

A hybrid plan recognition model for Alzheimer's patients: Interleaved-erroneous dilemma

Roy, P. C., Bouchard, B., Bouzouane, A., & Giroux, S. (2009) · Web Intelligence and Agent Systems An International Journal · doi:10.3233/wia-2009-0175 · Cited by 15

Learning object, grasping and manipulation activities using hierarchical HMMs

Patel, M., Miró, J. V., Kragić, D., Ek, C. H., & Dissanayake, G. (2014) · Autonomous Robots · doi:10.1007/s10514-014-9392-1 · Cited by 15

Spatio-temporal modeling of facial expressions using Gabor-wavelets and hierarchical hidden Markov models

Ma, L., Chelberg, D. M., & Çelenk, M. (2005) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2005.1529990 · Cited by 15

Self-Adaptive Healing for Containerized Cluster Architectures with Hidden Markov Models

Samir, A., & Pahl, C. (2019) · International Conference on Fog and Mobile Edge Computing (FMEC) · doi:10.1109/fmec.2019.8795322 · Cited by 15

Automatic language acquisition by an autonomous robot

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Automata Learning and Stochastic Modeling for Biosequence Analysis

Bejerano, G. (2003) · Cited by 15

How income satisfaction impacts driver engagement dynamics in ride-hailing services

Chen, X., Bai, S., Wei, Y., & Jiang, H. (2023) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2023.104418 · Cited by 14

Analyzing Activity Recognition Uncertainties in Smart Home Environments

Kim, E., Helal, S., Nugent, C., & Beattie, M. P. (2015) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2651445 · Cited by 14

Utilization of Time Series Tools in Life-sciences and Neuroscience

Gujral, H., Kushwaha, A. K., & Khurana, S. (2020) · Neuroscience Insights · doi:10.1177/2633105520963045 · Cited by 14

Hidden Markov Models Training by a Particle Swarm Optimization Algorithm

Aupetit, S., Monmarché, N., & Slimane, M. (2006) · Journal of Mathematical Modelling and Algorithms · doi:10.1007/s10852-005-9037-7 · Cited by 14

Modeling sequences of user actions for statistical goal recognition

Armentano, M. G., & Amandi, A. (2011) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-011-9103-y · Cited by 14

Clustering-Based Construction of Hidden Markov Models for Generative Kernels

Bicego, M., Cristani, M., Murino, V., Pękalska, E., & Duin, R. P. W. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-03641-5_35 · Cited by 14

Using Hidden Markov Models in Vehicular Crash Detection

Singh, G. B., & Song, H. (2009) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2008.928904 · Cited by 14

BILU-NEMH: A BILU neural-encoded mention hypergraph for mention extraction

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A Discriminative Model Corresponding to Hierarchical HMMs

Sugiura, T., Goto, N., & Hayashi, A. (2007) · Springer eBooks · doi:10.1007/978-3-540-77226-2_39 · Cited by 14

Learning Regular Expressions from Noisy Sequences

Galassi, U., & Giordana, A. (2005) · Lecture notes in computer science · doi:10.1007/11527862_7 · Cited by 14

Mobi-watchdog

Yan, G., Eidenbenz, S., & Sun, B. (2009) · Wireless Network Security · doi:10.1145/1514274.1514295 · Cited by 14

An Adversarial Hierarchical Hidden Markov Model for Human Pose Modeling and Generation

Zhao, R., & Ji, Q. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11860 · Cited by 14

A Machine Learning Approach to Test Data Generation: A Case Study in Evaluation of Gene Finders

Christiansen, H., & Dahmcke, C. M. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-73499-4_56 · Cited by 14

Product Named Entity Recognition Based on Hierarchical Hidden Markov Model ∗

Fei-fan, L., Zhao, J., Lv, B., Xu, B., & Yu, H. (2013) · Cited by 14

A Structured Variational Autoencoder for Contextual Morphological Inflection

Wolf-Sonkin, L., Naradowsky, J., Mielke, S. J., & Cotterell, R. (2018) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p18-1245 · Cited by 13

Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control

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Hierarchical Adversarial Inverse Reinforcement Learning

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Image Categorization Based on a Hierarchical Spatial Markov Model

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A Hierarchical Hidden Markov Model to support activities of daily living with an assistive robotic walker

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Multi-Platform Intelligent System for Multimodal Human-Computer Interaction

Jarosz, M., Nawrocki, P., Śnieżyński, B., & Indurkhya, B. (2021) · Computing and Informatics · doi:10.31577/cai_2021_1_83 · Cited by 13

Automatic Labeling of Sports Video Using Umpire Gesture Recognition

Chambers, G. S., Venkatesh, S., & WEST, G. A. W. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-27868-9_94 · Cited by 13

Decomposition in Hidden Markov Models for Activity Recognition

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Representing Conversations for Scalable Overhearing

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A Statistical Multiresolution Approach for Face Recognition Using Structural Hidden Markov Models

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Efficient Approximate Inference for Online Probabilistic Plan Recognition

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Hybrid Method in Identifying the Fraud Detection in the Credit Card

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Toward Efficient Bayesian Approaches to Inference in Hierarchical Hidden Markov Models for Inferring Animal Behavior

Sacchi, G., & Swallow, B. (2021) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2021.623731 · Cited by 12

Recognition of Driving Behavior in Electric Vehicle’s Li-Ion Battery Aging

Chou, K. S., Wong, K. L., Aguiari, D., Tse, R. T., Tang, S.-K., & Pau, G. (2023) · Applied Sciences · doi:10.3390/app13095608 · Cited by 12

Performance Evaluation with Hidden Markov Models

Silva, E. D. S. E., Leão, R. M. M., & Muntz, R. R. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-25575-5_10 · Cited by 12

Survey on classifying human actions through visual sensors

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An intelligent well-being monitoring system for residents in extra care homes

Jing, Y., Eastwood, M., Tan, B., Konios, A., Hamid, A., & Collinson, M. (2017) · Proceedings of the 1st International Conference on Internet of Things and Machine Learning · doi:10.1145/3109761.3109769 · Cited by 12

A New Framework for Modelling and Monitoring the Conversion of Cultivated Land to Built-up Land Based on a Hierarchical Hidden Semi-Markov Model Using Satellite Image Time Series

Yuan, Y., Lin, L., Chen, J., Hichem Sahli, B., Chen, Y., Wang, C., & Wu, B. (2019) · Remote Sensing · doi:10.3390/rs11020210 · Cited by 12

CrowdMeter: Gauging congestion level in railway stations using smartphones

Elhamshary, M., Youssef, M. A., Uchiyama, A., Hiromori, A., Yamaguchi, H., & Teruo Higashino, Y. (2019) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2019.04.005 · Cited by 12

Hierarchical Motion Segmentation Through sEMG for Continuous Lower Limb Motions

Park, S., Lee, D., Chung, W. K., & Kim, K. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2932343 · Cited by 12

Predicting packet loss statistics with hidden Markov models for FEC control

Silveira, F., & Silva, E. D. S. E. (2011) · Computer Networks · doi:10.1016/j.comnet.2011.10.009 · Cited by 12

Self-Similar Layered Hidden Markov Models

Adibi, J., & Shen, W. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44794-6_1 · Cited by 12

Unsupervised pattern discovery for multimedia sequences

Chang, S., & Xie, L. (2005) · Cited by 12

Machine listening for context-aware computing

Waibel, A., & Malkin, R. G. (2006) · Cited by 12

Identifying critical urban intersections from a fine-grained spatio-temporal perspective

Zhao, Z., Tang, L., Yang, X., Zhang, H., Li, G., & Li, Q. (2023) · Travel Behaviour and Society · doi:10.1016/j.tbs.2023.100649 · Cited by 11

Movement sequence analysis using hidden Markov models

Françoise, J., Roby-Brami, A., Riboud, N., & Bevilacqua, F. P. (2015) · International Conference on Movement and Computing (MOCO) · doi:10.1145/2790994.2791006 · Cited by 11

Intention Recognition in Human Machine Collaborative Systems

Aarno, D. (2007) · Cited by 11

Employing Grey Model forecasting GM(1,1) to historical medical sensor data towards system preventive in smart home e-health for elderly person

Jouini, R., Lemlouma, T., Maâlaoui, K., & Saidane, L. A. (2016) · International Wireless Communications and Mobile Computing Conference (IWCMC) · doi:10.1109/iwcmc.2016.7577210 · Cited by 11

A Controller Architecture for Anomaly Detection, Root Cause Analysis and Self-Adaptation for Cluster Architectures

Samir, A., & Pahl, C. (2019) · Open Repository and Bibliography (University of Luxembourg) · Cited by 11

Detection of DoS and DDoS Attacks Using Hidden Markov Model

Bharatwaj, M. B., Reddy, M. A., Kumar, T. S., & Vajipayajula, S. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-16-5529-6_74 · Cited by 11

Deep Learning for Lagrangian Drift Simulation at The Sea Surface

Botvynko, D., Granero-Belinchón, C., van Gennip, S. J., Benzinou, A., & Fablet, R. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10094622 · Cited by 11

Time space stochastic modelling of agricultural landscapes for environmental issues

Mari, J., Lazrak, E.-G., & Benoît, M. (2013) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2013.03.014 · Cited by 11

Conformation-Based Hidden Markov Models: Application to Human Face Identification

Bouchaffra, D. (2010) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2009.2039875 · Cited by 11

Audio-visual scene understanding utilizing text information for a cooking support robot

Kojima, R., Sugiyama, O., & Nakadai, K. (2015) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2015.7353973 · Cited by 11

Plan and Activity Recognition from a Topic Modeling Perspective

Freedman, R. G., Jung, H.-T., & Zilberstein, S. (2014) · Proceedings of the International Conference on Automated Planning and Scheduling · doi:10.1609/icaps.v24i1.13683 · Cited by 11

Human-guided robot 3D mapping using virtual reality technology

Du, J., Sheng, W., & Liu, M. (2016) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2016.7759680 · Cited by 11

A Relational Hierarchical Model for Decision-Theoretic Assistance

Natarajan, S., Tadepalli, P. V., & Fern, A. (2008) · Springer eBooks · doi:10.1007/978-3-540-78469-2_19 · Cited by 11

Hidden Markov Models Training Using Population-based Metaheuristics

Aupetit, S., Monmarché, N., & Slimane, M. (2007) · Springer eBooks · doi:10.1007/978-3-540-72960-0_20 · Cited by 11

Multistream Dynamic Bayesian Network for Meeting Segmentation

Dielmann, A., & Renals, S. J. (2005) · Lecture notes in computer science · doi:10.1007/978-3-540-30568-2_7 · Cited by 11

Real-time activity recognition from seismic signature via multi-scale symbolic time series analysis (MSTSA)

Sarkar, S., Damarla, T., & Ray, A. (2015) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2015.7172251 · Cited by 11

Hierarchical group process representation in multi-agent activity recognition

Zhang, W., Chen, F., Xu, W., & Du, Y. (2008) · Signal Processing Image Communication · doi:10.1016/j.image.2008.09.001 · Cited by 11

Multi-rate hidden Markov models and their application to machining tool-wear classification

Çetin, Ö., & Mari Ostendorf, E. (2004) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2004.1327241 · Cited by 11

Why are DBNs sparse

Chatterjee, S., & Russell, S. (2010) · Cited by 11

Bio-Inspired Formal Model for Space/Time Virtual Machine Randomization and Diversification

Ahmed, N. O., & Bhargava, B. (2020) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2020.2969353 · Cited by 11

Deep Knowledge Tracking based on Attention Mechanism for Student Performance Prediction

Liu, D., Dai, H., Zhang, Y., Li, Q., & Zhang, C. (2020) · IEEE International Conference on Computer Science and Educational Informatization (CSEI) · doi:10.1109/csei50228.2020.9142472 · Cited by 11

Multiple machine learning approach to characterize two-dimensional nanoelectronic devices via featurization of charge fluctuation

Lee, K., Nam, S., Ji, H., Choi, J., Jin, J.-E., Kim, Y., Na, J., Ryu, M.-Y., Cho, Y.-H., Lee, H., et al. (2021) · npj 2D Materials and Applications · doi:10.1038/s41699-020-00186-w · Cited by 11

Structural hidden Markov models: An application to handwritten numeral recognition

Bouchaffra, D., & Tan, J. (2006) · Intelligent Data Analysis · doi:10.3233/ida-2006-10105 · Cited by 11

Human activity learning and segmentation using partially hidden discriminative models

Bui, H., & Venkatesh, S. (2005) · Cited by 11

Fisher Kernels for Logical Sequences

Kersting, K., & Gärtner, T. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30115-8_21 · Cited by 11

Discovering Compositional Structure

Harrison, M. T. (2005) · Cited by 11

Kalman Filter Demystified: From Intuition to Probabilistic Graphical Model to Real Case in Financial MarketsPreprint

Benhamou, E. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3292762 · Cited by 11

Context-sensitive learning for enhanced audiovisual emotion classification (Extended abstract)

Metallinou, A., Katsamanis, A., Wöllmer, M., Eyben, F., Schuller, B. W., & Narayanan, S. S. (2015) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2015.7344611 · Cited by 10

Infinite Hierarchical Hidden Markov Models

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Hidden Markov Models (HHMMs). HHMMs

Heller, K., Teh, Y. W., & Görür, D. (2010)

Topology Estimation of Hierarchical Hidden Markov Models for Language Models

Wakabayashi, K., & Miura, T. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13881-2_13 · Cited by 2

Techniques to incorporate the benefits of a hierarchy in a modified hidden Markov model

Chou, L.-Y. (2006) · International Conference on Computational Linguistics and Annual Meeting of the Association for Computational Linguistics (COLING/ACL) · doi:10.3115/1273073.1273089 · Cited by 5