5 papers
Loss Function Design for Deep Unfolded Sparse Signal Recovery: Supervised and Unsupervised Learning
Koshi Nagahisa, Ryo Hayakawa, Youji Iiguni
This paper investigates the impact of loss function design in deep unfolding techniques for sparse signal recovery algorithms. We focus on deep unfolded versions of the fundamental…
LLMs-Integrated Automatic Hate Speech Recognition Using Controllable Text Generation Models
Ryutaro Oshima, Yuya Hosoda, Youji Iiguni
This paper proposes an automatic speech recognition (ASR) model for hate speech using large language models (LLMs). The proposed method integrates the encoder of the ASR model with…
Optimization-Based Image Restoration under Implementation Constraints in Optical Analog Circuits
Taisei Kato, Ryo Hayakawa, Soma Furusawa +2
Optical analog circuits have attracted attention as promising alternatives to traditional electronic circuits for signal processing tasks due to their potential for low-latency and…
Depth-Aided Color Image Inpainting in Quaternion Domain
Shunki Tatsumi, Ryo Hayakawa, Youji Iiguni
In this paper, we propose a depth-aided color image inpainting method in the quaternion domain, called depth-aided low-rank quaternion matrix completion (D-LRQMC). In conventional…
Deep Unfolding-Aided Parameter Tuning for Plug-and-Play-Based Video Snapshot Compressive Imaging
Takashi Matsuda, Ryo Hayakawa, Youji Iiguni
Snapshot compressive imaging (SCI) captures high-dimensional data efficiently by compressing it into two-dimensional observations and reconstructing high-dimensional data from two-…