351 citations · 395 across the 10 of their papers we have counts for
10 papers
Watch from sky: machine-learning-based multi-UAV network for predictive police surveillance
Ryusei Sugano, Ryoichi Shinkuma, Takayuki Nishio +2
This paper presents the watch-from-sky framework, where multiple unmanned aerial vehicles (UAVs) play four roles, i.e., sensing, data forwarding, computing, and patrolling, for pre…
Communication-oriented Model Fine-tuning for Packet-loss Resilient Distributed Inference under Highly Lossy IoT Networks
Sohei Itahara, Takayuki Nishio, Yusuke Koda +1
The distributed inference (DI) framework has gained traction as a technique for real-time applications empowered by cutting-edge deep machine learning (ML) on resource-constrained…
Bi-directional Beamforming Feedback-based Firmware-agnostic WiFi Sensing: An Empirical Study
S. Kondo, S. Itahara, K. Yamashita +4
In the field of WiFi sensing, as an alternative sensing source of the channel state information (CSI) matrix, the use of a beamforming feedback matrix (BFM)that is a right singular…
Frame-Capture-Based CSI Recomposition Pertaining to Firmware-Agnostic WiFi Sensing
Ryosuke Hanahara, Sohei Itahara, Kota Yamashita +4
With regard to the implementation of WiFi sensing agnostic according to the availability of channel state information (CSI), we investigate the possibility of estimating a CSI matr…
Beamforming Feedback-based Model-Driven Angle of Departure Estimation Toward Legacy Support in WiFi Sensing: An Experimental Study
Sohei Itahara, Sota Kondo, Kota Yamashita +3
This study experimentally validated the possibility of angle of departure (AoD) estimation using multiple signal classification (MUSIC) with only WiFi control frames for beamformin…
Computer Vision-assisted Single-antenna and Single-anchor RSSI Localization Harnessing Dynamic Blockage Events
Tomoya Sunami, Sohei Itahara, Yusuke Koda +2
This paper demonstrates the feasibility of single-antenna and single-RF (radio frequency)- anchor received power strength indicator (RSSI) localization (SARR-LOC) with the assistan…
Packet-Loss-Tolerant Split Inference for Delay-Sensitive Deep Learning in Lossy Wireless Networks
Sohei Itahara, Takayuki Nishio, Koji Yamamoto
The distributed inference framework is an emerging technology for real-time applications empowered by cutting-edge deep machine learning (ML) on resource-constrained Internet of th…
Online Trainable Wireless Link Quality Prediction System using Camera Imagery
Sohei Itahara, Takayuki Nishio, Masahiro Morikura +1
Machine-learning-based prediction of future wireless link quality is an emerging technique that can potentially improve the reliability of wireless communications, especially at hi…
Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data
Sohei Itahara, Takayuki Nishio, Yusuke Koda +2
This study develops a federated learning (FL) framework overcoming largely incremental communication costs due to model sizes in typical frameworks without compromising model perfo…
Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning
Sohei Itahara, Takayuki Nishio, Masahiro Morikura +1
Federated learning (FL) enables a neural network (NN) to be trained using privacy-sensitive data on mobile devices while retaining all the data on their local storages. However, FL…