郭　鵬宇さん（電気系工学専攻・中山研究室・D3）がSPML 2025においてBest Presentation Awardを受賞しました。

<受賞した賞の名称と簡単な説明>
Best Presentation Award 本賞は、SPML 2025の各セッションにおいて優れたプレゼンテーションを表彰するものです。

<受賞された研究・活動について>
Pengyu Guo, Masaya Nakayama, CNN-Transformer-Bi-LSTM: A Hybrid Deep Learning Framework for Wearable Sensor-based Human Activity Recognition, 2025 IEEE 8th International Conference on Signal Processing and Machine Learning (SPML 2025), July, 2025. Human activity recognition (HAR) focuses on identifying and classifying human activities based on data collected from various sources. Its importance lies in its wide range of applications, especially in health monitoring, safety enhancement, efficiency, and quality of life improvement. In this work, we propose a CNN-Transformer-Bi-LSTM (CTBL) hybrid framework for wearable sensor HAR, integrating CNN for local feature extraction, Transformer encoder for long-range temporal modeling, and BiLSTM layers for bidirectional sequential learning. We evaluate our model on four benchmark datasets (MobiAct, UniMiB SHAR, UCI HAR, USC-HAD), achieving F1 scores of 91.25%, 93.14%, 89.59%, and 91.46%, respectively. Further analysis shows that the CNN layers contribute significantly to the classification of static activities, while the Bi- LSTM improves the recognition of symmetric transitional motions, highlighting the impact of different model components on HAR performance.

<今後の抱負・感想>
この度は最優秀スピーチ賞を受賞することができ、大変光栄に存じます。また、本研究を指導していただいた中山雅哉先生に感謝申し上げます。今後も続いて研究を進みます。