Shigeo Abe is affiliated with Kobe University in Japan and specializes primarily in computer science, engineering, and physics and astronomy. Their research covers several subfields, including computer vision and pattern recognition, artificial intelligence, media technology, astronomy and astrophysics, and control and systems engineering.
Their work has engaged with various main topics, particularly face and expression recognition, remote-sensing image classification, machine learning and algorithms, neural networks and applications, machine learning and extreme learning machines (ELM), advanced algorithms and applications, and blind source separation techniques.
Recent publications by Shigeo Abe include:
Collaboration is part of their work, with frequent coauthors including Eleanor K. Sansom, Hadrien A. R. Devillepoix, Masayoshi Yamamoto, Satoshi Nozawa, and M. C. Towner.
Shigeo Abe's research has appeared in several publication venues, notably Computers, the 2022 International Joint Conference on Neural Networks (IJCNN), and arXiv (Cornell University).
Shigeo Abe
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S. Abe;Ming-Shong Lan
T. Inoue;S. Abe
Daisuke Tsujinishi;Shigeo Abe
S. Abe;Ming-Shong Lan
S. Abe;R. Thawonmas
Shigeo Abe;Takuya Inoue
F. Takahashi;S. Abe
Shigeo Abe
Shigeo Abe
V. Uebele;S. Abe;Ming-Shong Lan
Shigeo Abe;Anca Ralescu
Seiichi Ozawa;Soon Lee Toh;Shigeo Abe;Shaoning Pang
S. Abe
Seiichi Ozawa;Soon Lee Toh;Shigeo Abe;Shaoning Pang
Shigeo Abe
Shigeo Abe
Shigeo Abe
S. Abe;T. Bandoh;S. Yamaguchi;K. Kurosawa
R. Thawonmas;S. Abe
Shigeo Abe;Junzo Kawakami;Kotaroo Hirasawa
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