arXiv subjects

Hajime Suzuki

Publications and source records attributed to Hajime Suzuki.

21 records · Page 2Linked to original sources

arXiv2023

Development of a Novel Quantum Pre-processing Filter to Improve Image Classification Accuracy of Neural Network Models

This paper proposes a novel quantum pre-processing filter (QPF) to improve the image classification accuracy of neural network (NN) models. A simple four qubit quantum circuit that uses Y rotation gates for encoding and two controlled NOT gates for creating correlation among the qubits is applied as a feature extraction filter prior to passing data into the fully connected NN architecture. By applying the QPF approach, the results show that the image classification accuracy based on the MNIST (handwritten 10 digits) and the EMNIST (handwritten 47 class digits and letters) datasets can be improved, from 92.5% to 95.4% and from 68.9% to 75.9%, respectively. These improvements were obtained without introducing extra model parameters or optimizations in the machine learning process. However, tests performed on the developed QPF approach against a relatively complex GTSRB dataset with 43 distinct class real-life traffic sign images showed a degradation in the classification accuracy. Considering this result, further research into the understanding and the design of a more suitable quantum circuit approach for image classification neural networks could be explored utilizing the baseline method proposed in this paper.

quant-ph↗

arXiv2021

Heterogeneous Ground and Air Platforms, Homogeneous Sensing: Team CSIRO Data61's Approach to the DARPA Subterranean Challenge

Heterogeneous teams of robots, leveraging a balance between autonomy and human interaction, bring powerful capabilities to the problem of exploring dangerous, unstructured subterranean environments. Here we describe the solution developed by Team CSIRO Data61, consisting of CSIRO, Emesent and Georgia Tech, during the DARPA Subterranean Challenge. These presented systems were fielded in the Tunnel Circuit in August 2019, the Urban Circuit in February 2020, and in our own Cave event, conducted in September 2020. A unique capability of the fielded team is the homogeneous sensing of the platforms utilised, which is leveraged to obtain a decentralised multi-agent SLAM solution on each platform (both ground agents and UAVs) using peer-to-peer communications. This enabled a shift in focus from constructing a pervasive communications network to relying on multi-agent autonomy, motivated by experiences in early circuit events. These experiences also showed the surprising capability of rugged tracked platforms for challenging terrain, which in turn led to the heterogeneous team structure based on a BIA5 OzBot Titan ground robot and an Emesent Hovermap UAV, supplemented by smaller tracked or legged ground robots. The ground agents use a common CatPack perception module, which allowed reuse of the perception and autonomy stack across all ground agents with minimal adaptation.

cs.RO↗

arXiv2018

Construction of Adaptive Short LDPC Codes for Distributed Transmit Beamforming

One of the challenges often faced with wireless communication systems is its limited range and data-rate. Distributed Transmit Beamforming (DTB) techniques are being developed to address these two issues to provide reliable connectivity from power-limited distributed users. This paper proposes an adaptive Low Density Parity Check (LDPC) coding scheme for the DTB system. The proposed scheme constructs powerful LDPC codes with varying code-rates and block-lengths. This feature of the proposed scheme allows the DTB system to optimise its system resources, improve throughput and communicate reliably under large variation of different channel environments. The performance of some of the codes constructed using the proposed scheme is evaluated and compared with the uncoded and other coded-DTB systems. The results obtained show large gains over the compared systems. The results also show that coding applied to the DTB system drastically reduces the minimum number of distributed transmit nodes required to achieve a target error-rate with the same energy per information bit to noise power spectral density.

eess.SP↗