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Computer Science

D-Index
36
Citations
5064
World Ranking
11314
National Ranking
4666

Overview

Thomas Plötz is affiliated with the Georgia Institute of Technology in the United States. Their research primarily spans the field of Computer Science, with a focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Biomedical Engineering, and Computer Science Applications.

The main topics addressed in their work include Context-Aware Activity Recognition Systems, Human Pose and Action Recognition, Anomaly Detection Techniques and Applications, IoT and Edge/Fog Computing, Non-Invasive Vital Sign Monitoring, Mobile Crowdsensing and Crowdsourcing, and Technology Use by Older Adults.

Plötz's publications appear frequently in several venues, most notably in the Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, arXiv (Cornell University), Sensors, ACM Transactions on Computing for Healthcare, and ACM Transactions on Interactive Intelligent Systems.

Notable recent papers include:

  • IMUTube, 2020, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • Assessing the State of Self-Supervised Human Activity Recognition Using Wearables, 2022, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • Explainable Activity Recognition for Smart Home Systems, 2023, ACM Transactions on Interactive Intelligent Systems
  • Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor, 2020, IEEE Journal of Biomedical and Health Informatics
  • Approaching the Real-World, 2021, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies

Plötz has collaborated frequently with several co-authors, including:

  • Hyeokhyen Kwon
  • Gregory D. Abowd
  • Harish Haresamudram
  • Zikang Leng
  • Sonia Chernova

Best Publications

  • Deep, convolutional, and recurrent models for human activity recognition using wearables

    Nils Y. Hammerla;Shane Halloran;Thomas Plötz

  • Ensembles of Deep LSTM Learners for Activity Recognition using Wearables

    Yu Guan;Thomas Plötz

  • Feature learning for activity recognition in ubiquitous computing

    Thomas Plötz;Nils Y. Hammerla;Patrick Olivier

  • Markov models for offline handwriting recognition: a survey

    Thomas Plötz;Gernot A. Fink

  • The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

    Matthias Kranz;Andreas MöLler;Nils Hammerla;Stefan Diewald

  • Early detection of health and welfare compromises through automated detection of behavioural changes in pigs

    Stephen G. Matthews;Amy L. Miller;James Clapp;Thomas Plötz

  • PD disease state assessment in naturalistic environments using deep learning

    Nils Y. Hammerla;James M. Fisher;Peter Andras;Lynn Rochester

  • Optimising sampling rates for accelerometer-based human activity recognition

    Aftab Khan;Nils Hammerla;Sebastian Mellor;Thomas Plötz

  • Automated tracking to measure behavioural changes in pigs for health and welfare monitoring.

    Stephen G. Matthews;Amy L. Miller;Thomas PlÖtz;Thomas PlÖtz;Ilias Kyriazakis

  • Multi-modal anchoring for human–robot interaction

    Jannik Fritsch;Marcus Kleinehagenbrock;Sebastian Lang;Thomas Plötz

  • Automatic assessment of problem behavior in individuals with developmental disabilities

    Thomas Plötz;Nils Y. Hammerla;Agata Rozga;Andrea Reavis

  • Using unlabeled data in a sparse-coding framework for human activity recognition

    Sourav Bhattacharya;Petteri Nurmi;Nils Hammerla;Thomas Plötz

  • Movement recognition technology as a method of assessing spontaneous general movements in high risk infants.

    Claire Marcroft;Claire Marcroft;Aftab Khan;Nicholas D. Embleton;Michael Trenell

  • Rapid specification and automated generation of prompting systems to assist people with dementia

    Jesse Hoey;Thomas Plötz;Dan Jackson;Andrew Monk

  • ClimbAX: skill assessment for climbing enthusiasts

    Cassim Ladha;Nils Y. Hammerla;Patrick Olivier;Thomas Plötz

  • IMUTube: Automatic Extraction of Virtual on-body Accelerometry from Video for Human Activity Recognition

    Hyeokhyen Kwon;Catherine Tong;Harish Haresamudram;Yan Gao

  • Dog's life: wearable activity recognition for dogs

    Cassim Ladha;Nils Hammerla;Emma Hughes;Patrick Olivier

  • Masked reconstruction based self-supervision for human activity recognition

    Harish Haresamudram;Apoorva Beedu;Varun Agrawal;Patrick L. Grady

  • Let's (not) stick together: pairwise similarity biases cross-validation in activity recognition

    Nils Y. Hammerla;Thomas Plötz

  • Assessing the State of Self-Supervised Human Activity Recognition Using Wearables

    Unknown

  • On attention models for human activity recognition.

    Vishvak S. Murahari;Thomas Plötz

  • Deep Learning for Human Activity Recognition in Mobile Computing

    Thomas Plotz;Yu Guan

  • GymSkill: A personal trainer for physical exercises

    Andreas Moller;Luis Roalter;Stefan Diewald;Johannes Scherr

  • Prediction of Mood Instability with Passive Sensing

    Mehrab Bin Morshed;Koustuv Saha;Richard Li;Sidney K. D'Mello

  • On the role of features in human activity recognition

    Harish Haresamudram;David V. Anderson;Thomas Plötz

  • Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework

    Aftab Khan;James Nicholson;Sebastian Mellor;Daniel Jackson

Frequent Co-Authors

Gernot A. Fink
Gernot A. Fink TU Dortmund University
Patrick Olivier
Patrick Olivier Monash University
Gregory D. Abowd
Gregory D. Abowd Northeastern University
Ilias Kyriazakis
Ilias Kyriazakis Queen's University Belfast
Irfan Essa
Irfan Essa Georgia Institute of Technology
David Kirk
David Kirk Newcastle University
Kristof Van Laerhoven
Kristof Van Laerhoven University of Siegen
Stephen J. McKenna
Stephen J. McKenna University of Dundee
Munmun De Choudhury
Munmun De Choudhury Georgia Institute of Technology
Sandra A. Edwards
Sandra A. Edwards Newcastle University

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