collaborators

5 papers

cs.RO2026

A Low-Cost Hybrid Reservoir Computing Model for Isolated Sign Language Video Recognition

Nitin Kumar Singh, Arie Rachmad Syulistyo, Yuichiro Tanaka +1

Sign language recognition (SLR) enhances communication between hearing and hearing-impaired individuals. Although deep learning (DL) has achieved promising performance in SLR, its…

cs.AR2026

CBM-Dual: A 65-nm Fully Connected Chaotic Boltzmann Machine Processor for Dual Function Simulated Annealing and Reservoir Computing

Kanta Yoshioka, Soshi Hirayae, Yuichiro Tanaka +3

This paper presents CBM-Dual, the first silicon-proven digital chaotic dynamics processor (CDP) supporting both simulated annealing (SA) and reservoir computing (RC). CBM-Dual enab…

cs.CL2025

Reservoir Computing inspired Matrix Multiplication-free Language Model

Takumi Shiratsuchi, Yuichiro Tanaka, Hakaru Tamukoh

Large language models (LLMs) have achieved state-of-the-art performance in natural language processing; however, their high computational cost remains a major bottleneck. In this s…

cs.CV2025

Sign Language Recognition using Parallel Bidirectional Reservoir Computing

Nitin Kumar Singh, Arie Rachmad Syulistyo, Yuichiro Tanaka +1

Sign language recognition (SLR) facilitates communication between deaf and hearing communities. Deep learning based SLR models are commonly used but require extensive computational…

cs.RO2025

Sign Language Recognition using Bidirectional Reservoir Computing

Nitin Kumar Singh, Arie Rachmad Syulistyo, Yuichiro Tanaka +1

Sign language recognition (SLR) facilitates communication between deaf and hearing individuals. Deep learning is widely used to develop SLR-based systems; however, it is computatio…