Vito Janko

发表

Activity and stress monitoring using smartphone and wrist device

M. Gams, M. Luštrek, H. Gjoreski, 2016 .

Optimizing non-pharmaceutical intervention strategies against COVID-19 using artificial intelligence

M. Gams, Tea Tusar, M. Luštrek, 2021, Frontiers in Public Health.

What Actually Works for Activity Recognition in Scenarios with Significant Domain Shift: Lessons Learned from the 2019 and 2020 Sussex-Huawei Challenges

M. Gams, M. Luštrek, Andrejaana Andova, 2022, Sensors.

Constrained Multiobjective Optimization for the Design of Energy-Efficient Context Recognition Systems

Mitja Lustrek, Bogdan Filipic, Vito Janko, 2020, BIOMA.

Real-time activity monitoring with a wristband and a smartphone

Vito Janko, Mitja Luštrek, Robert Szeklicki, 2017, Information Fusion.

Classical and deep learning methods for recognizing human activities and modes of transportation with smartphone sensors

Jani Bizjak, Martin Gjoreski, Matjaž Gams, 2020, Inf. Fusion.

Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of COVID-19

M. Gams, M. Luštrek, Vito Janko, 2021, International journal of environmental research and public health.

e-Gibalec: Mobile application to monitor and encourage physical activity in schoolchildren

Anton Gradisek, Mitja Lustrek, Vito Janko, 2017, J. Ambient Intell. Smart Environ..

A New Frontier for Activity Recognition: The Sussex-Huawei Locomotion Challenge

Jani Bizjak, Matjaz Gams, Martin Gjoreski, 2018, UbiComp/ISWC Adjunct.

Activity Recognition for Diabetic Patients Using a Smartphone

Alfonso E. Romero, Mitja Lustrek, Kostas Stathis, 2016, Journal of Medical Systems.

Cross-location transfer learning for the sussex-huawei locomotion recognition challenge

Matjaz Gams, Martin Gjoreski, Mitja Lustrek, 2019, UbiComp/ISWC Adjunct.