｜ program
Program
Proceedings
The accepted papers in HASCA workshop are included in the proceedings on ACM DL.
https://dl.acm.org/doi/proceedings/10.1145/3460418
Workshop starts at September 25th (PDT) / 26th (EDT, CEST, JST), 2021.
When you join, please search "HASCA" on Whova Agenda and get the links for zoom/gather.town.
Presentation time:
HASCA oral presentation, 15 min (12-min talk + 3-min Q&A)
(For short paper, 8min talk + 2min Q&A)
SHL oral presentation, 12 min (10-min talk + 2-min Q&A)
SHL video, 1 min
Nurse oral presentation, 12 min
Nurse video, 1 min
| 2200-0027(PDT) 0100-0327(EDT) 0700-0927(CEST) 14:00-1627(JST) | -Opening remarks [SHL Session (chair: Paula Lago)] -SHL introduction [4 min] -SHL summary [15 min] Locomotion and Transportation Mode Recognition from GPS and radio signals: Summary of SHL Challenge 2021. -SHL team 1 presentation [12 min] -SHL team 2 presentation [12 min] -SHL team 3 presentation [12 min] -SHL Challenge videos broadcast [11 min] Dense CNN and IndRNN for the Sussex-Huawei Locomotion-Transportation Recognition Challenge. Transition-points-based Segmentation and Hierarchical Classification for Locomotion and Transportation recognition Radio-data. Triple-O for SHL Recognition Challenge: An Ensemble Framework for Multi-class Imbalance and Training-testing Distribution Inconsistency by OvO Binarization with Confidence Weight of One-class Classification. A Windowless Approach to Recognize Various Modes of Locomotion and Transportation. An Ensemble of ConvTransformer Networks for the Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenge. Locomotion-Transportation Recognition via LSTM and GPS Derived Feature Engineering from Cell Phone Data. Location-based Human Activity Recognition Using Long-term Deep Learning Invariant Mapping. Classical Machine Learning Approach for Human Activity Recognition Using Location Data. Multiple Tree Model Integration for Transportation Mode Recognition. Classical machine learning and deep neural network ensemble model for GPS-based activity recognition. Phased Human Activity Recognition based on GPS. -SHL ceremony (5 min) [HASCA Session 1 (chair: Yu Enokibori)] -[HASCA] Collecting a dataset of gestures for skill assessment in the field: a beach volleyball serves case study Mathias Ciliberto, Luis Alejandro Ponce Cuspinera, Daniel Roggen -[HASCA] Reducing Label Fragmentation during Time-series Data Annotation to Reduce Annotation Costs Joseph Korpela, Takayuki Akiyama, Takehiro Niikura, Katsuyuki Nakamura -[HASCA] Prediction of Eating Activity using Smartwatch Haruka Kamachi, Tahera Hossain, Fuyuka Tokuyama, Anna Yokokubo, Guillaume Lopez -[HASCA] [Short Paper] Inferring complex textile shape from an integrated carbon black-infused ecoflex-based bend and stretch sensor array Leonardo Azael Garcia-Garcia, George Valsamakis, Paul Kreitmair, Niko Munzenrieder, Daniel Roggen -[HASCA] Automatic Segmentation Method of Bone Conduction Sound for Eating Activity Detailed Detection Haruka Kamachi, Takumi Kondo, Tahera Hossain, Anna Yokokubo, Guillaume Lopez |
| 0027-0050(PDT) 0327-0350(EDT) 0927-0950(CEST) 1627-1650(JST) | Break/ SHL poster session [about 30 min] |
| 0050-0233(PDT) 0350-0533(EDT) 0950-1133(CEST) 1650-1833(JST) | [Nurse Session (chair: Sozo Inoue)] -Nurse summary [12 min] Summary of the Third Nurse Care Activity Recognition Challenge - Can We Do from the Field Data? -Nurse winner presentation [12 min] -Nurse videos broadcast [3min] -Nurse ceremony Nurse papers: - Nurse Care Activity Recognition from Accelerometer Sensor Data Using Fourier- and Wavelet-based Features M. Ashikuzzaman Kowshik,Yeasin Arafat Pritom,Md.Sohanur Rahman,Ali Akbar,Md Atiqur Rahman Ahad [PDF][Video] - Nurse Care Activity Recognition: A Cost-Sensitive Ensemble Approach to Handle Imbalanced Class Problem in the Wild Arafat Rahman,Iqbal Hassan,Md Atiqur Rahman Ahad [PDF][Video] - Feature-based Method for Nurse Care Complex Activity Recognition from Accelerometer Sensor Faizul Rakib Sayem,MD Mamun Sheikh,Md Atiqur Rahman Ahad [PDF][Video] - Accelerometer based Complex Nurse Care Activity Recognition using Machine Learning Approach Zubair Rahman Tusar,Maksuda Islam,Sadia Sharmin [PDF][Video] [HASCA Session 2 (chair Kazuya Murao)] -[HASCA] Activity Knowledge Graph Recognition by Eye Gaze: Identification of Distant Object in Eye Sight for Watch Activity Yuki Toyosaka, Tsuyoshi Okita -[HASCA] Toward Fine-Grained Sleeping Activity Recognition: 3d Extension and an Estimation Try on Joint Position of SLP Dataset Hiroki Kato, Yu Enokibori, Naoto Yoshida, Kenji Mase -[HASCA] Analysis of Feature Importances for Automatic Generation of Care Records Haru Kaneko, Tahera Hossain, Sozo Inoue -[HASCA] PerMML: A Performance Metric for Multi-layer Dataset Sayeda Shamma Alia, Tahera Hossain, Sozo Inoue -Closing remarks |