8 citations · 18 across the 4 of their papers we have counts for
5 papers
Toward Pioneering Sensors and Features Using Large Language Models in Human Activity Recognition
Haru Kaneko, Sozo Inoue
In this paper, we propose a feature pioneering method using Large Language Models (LLMs). In the proposed method, we use Chat-GPT 1 to find new sensor locations and new features. T…
Translation Between Waves, wave2wave
Tsuyoshi Okita, Hirotaka Hachiya, Sozo Inoue +1
The understanding of sensor data has been greatly improved by advanced deep learning methods with big data. However, available sensor data in the real world are still limited, whic…
A dataset for complex activity recognition withmicro and macro activities in a cooking scenario
Paula Lago, Shingo Takeda, Sayeda Shamma Alia +4
Complex activity recognition can benefit from understanding the steps that compose them. Current datasets, however, are annotated with one label only, hindering research in this di…
Achieving Single-Sensor Complex Activity Recognition from Multi-Sensor Training Data
Paula Lago, Moe Matsuki, Sozo Inoue
In this study, we propose a method for single sensor-based activity recognition, trained with data from multiple sensors. There is no doubt that the performance of complex activity…
Deep Recurrent Neural Network for Mobile Human Activity Recognition with High Throughput
Masaya Inoue, Sozo Inoue, Takeshi Nishida
In this paper, we propose a method of human activity recognition with high throughput from raw accelerometer data applying a deep recurrent neural network (DRNN), and investigate v…