Name
Affiliation
Papers
SOZO INOUE
Kyushu Univ, Higashi Ku, Fukuoka 8128580, Japan
102
Collaborators
Citations 
PageRank 
163
176
58.17
Referers 
Referees 
References 
437
928
393
Search Limit
100928
Title
Citations
PageRank
Year
Detection of Infectious Respiratory Disease Through Sweat From Axillary Using an E-Nose With Stacked Deep Neural Network00.342022
Toward the Analysis of Office Workers’ Mental Indicators Based on Wearable, Work Activity, and Weather Data00.342021
On-Device Deep Personalization For Robust Activity Data Collection00.342021
Using LUPI to Improve Complex Activity Recognition00.342021
CrowdAct: Achieving High-Quality Crowdsourced Datasets in Mobile Activity Recognition.10.342021
Integrating a spoken dialogue system, nursing records, and activity data collection based on smartphones00.342021
Using additional training sensors to improve single-sensor complex activity recognition10.342021
Transition-points-based Segmentation and Hierarchical Classification for Locomotion and Transportation recognition on Radio-data00.342021
Analysis of Feature Importances for Automatic Generation of Care Records00.342021
Summary of the Third Nurse Care Activity Recognition Challenge - Can We Do from the Field Data?00.342021
PerMML: A Performance Metric for Multi-layer Dataset00.342021
A Method for Sensor-Based Activity Recognition in Missing Data Scenario.00.342020
WorkerSense: Mobile Sensing Platform for Collecting Physiological, Mental, and Environmental State of Office Workers00.342020
Improving fine-tuned question answering models for electronic health records00.342020
MCoMat: a new performance metric for imbalanced multi-layer activity recognition dataset00.342020
Improving activity data collection with on-device personalization using fine-tuning00.342020
Wearable Sensor-Based Gait Analysis for Age and Gender Estimation.00.342020
Summary of the 2nd nurse care activity recognition challenge using lab and field data00.342020
UPIC: user and position independent classical approach for locomotion and transportation modes recognition00.342020
Evaluating a Spoken Dialogue System for Recording Systems of Nursing Care.00.342019
Position independent activity recognition using shallow neural architecture and empirical modeling00.342019
Human activity recognition using earable device00.342019
On-Device Deep Learning Inference for Efficient Activity Data Collection.00.342019
Nurse care activity recognition challenge: summary and results00.342019
OU-ISIR Wearable Sensor-based Gait Challenge: Age and Gender00.342019
Characterizing Word Embeddings for Zero-Shot Sensor-Based Human Activity Recognition.10.372019
Sensor-Based Daily Activity Understanding in Caregiving Center10.632019
Integrating Activity Recognition and Nursing Care Records: The System, Deployment, and a Verification Study00.342019
Evaluation Of Transfer Learning For Human Activity Recognition Among Different Datasets00.342019
Optimizing activity data collection with gamification points using uncertainty based active learning00.342019
A dialogue-based annotation for activity recognition00.342019
Reduction of marker-body matching work in activity recognition using motion capture00.342019
Towards pervasive geospatial affect perception.10.412018
Machine Learning of User Attentions in Sensor Data Visualization.00.342018
Study of LoRaWAN Technology for Activity Recognition.20.362018
A Hybrid Model Using Hidden Markov Chain and Logic Model for Daily Living Activity Recognition.00.342018
Gamification for High-Quality Dataset in Mobile Activity Recognition.10.372018
Deep recurrent neural network for mobile human activity recognition with high throughput70.522018
Sensing Experiment in a Caregiving Facility for Correlation Analysis of Sleep and Daytime Activities.00.342018
A Multi-Sensor Setting Activity Recognition Simulation Tool.00.342018
A Mobile App for Nursing Activity Recognition.00.342018
Improving Sensor-based Activity Recognition Using Motion Capture as Additional Information.00.342018
Supervised and Neural Classifiers for Locomotion Analysis.00.342018
Pre-Consulting Dialogue Systems for Telemedicine: Yes/No Intent Classification.00.342018
Activity Recognition: Translation across Sensor Modalities Using Deep Learning.00.342018
Dialogue Breakdown Detection with Long Short Term Memory.00.342018
Activity Recognition by Using LoRaWAN Sensor.20.362018
5th Int. workshop on human activity sensing corpus and applications (HASCA): towards open-ended context awareness.10.412017
Recognition of multiple overlapping activities using compositional CNN-LSTM model.20.362017
Mobile Activity Recognition through Training Labels with Inaccurate Activity Segments.20.382016
  • 1
  • 2