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Temporal convolutional neural networks to generate a head-related impulse response from one direction to another

Autor: Kobayashi, Tatsuki, Maruyama, Yoshiko, Nambu, Isao, Yano, Shohei, Wada, Yasuhiro

Virtual sound synthesis is a technology that allows users to perceive spatial sound through headphones or earphones. However, accurate virtual sound requires an individual head-related transfer function (HRTF), which can be difficult to measure due t

Externí odkaz: http://arxiv.org/abs/2310.14018

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Sliding-Window Normalization to Improve the Performance of Machine-Learning Models for Real-Time Motion Prediction Using Electromyography

Autor: Tanaka, Taichi, Nambu, Isao, Maruyama, Yoshiko, Wada, Yasuhiro

Publikováno v: Sensors 2022, 22(13)

Many researchers have used machine learning models to control artificial hands, walking aids, assistance suits, etc., using the biological signal of electromyography (EMG). The use of such devices requires high classification accuracy of machine lear

Externí odkaz: http://arxiv.org/abs/2205.09301

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Accuracy Enhancement for Ear Acoustic Authentication Using Between-class Features

Autor: Yasuhara, Masaki, Nambu, Isao, Maruyama, Yoshiko, Yano, Shohei

In existing biometric authentication methods, the user must perform an authentication operation such as placing a finger in a scanner or facing a camera. With ear acoustic authentication, acoustic characteristics of the ear canal are used as biometri

Externí odkaz: http://arxiv.org/abs/2205.08778

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