慶應義塾研究者情報データベース

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• Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge

  W Bulten, K Kartasalo, PHC Chen, P Ström, H Pinckaers, K Nagpal, Y Cai, ...

  Nature medicine, 1-10 2022年

• Time-Based Current Source: A Highly Digital Robust Current Generator for Switched Capacitor Circuits

  K YOSHIOKA

  IEICE Transactions on Electronics, 2021CDP0002 2022年

• VCO-Based Comparator: A Fully Adaptive Noise Scaling Comparator for High-Precision and Low-Power SAR ADCs

  Yoshioka K.

  IEEE Transactions on Very Large Scale Integration (VLSI) Systems （IEEE Transactions on Very Large Scale Integration (VLSI) Systems)  29 （ 12 ） 2143 - 2152 2021年12月

  ISSN  10638210

  　概要を見る

  A voltage-controlled oscillator (VCO)-based comparator that automatically adapts its noise performance reflecting the input voltage difference ( $\Delta V_{\text {in}}$ ) is presented. Such adaptive operation significantly reduces the power of high-precision comparators in successive-approximation-register (SAR) ADCs. $\Delta V_{\text {in}}$ is integrated as a time difference via the VCO, where the integration continues as long as the time difference is below a certain threshold, defined by the phase detector deadzone. Thus, when $\Delta V_{\text {in}}$ is large, the comparator operates as a low-power delay line-based comparator, and with small $\Delta V_{\text {in}}$ , the VCO oscillates to integrate the input signal and suppresses the comparator noise. The required oscillations to complete the comparison are inversely proportional to $\Delta V_{\text {in}}$ , realizing fully adaptive noise and power scaling. This article provides a detailed analysis and specific design guidelines of the VCO comparator. Moreover, the PVT drift tolerance and detailed circuit implementations are deeply discussed as well. For proof-of-concept, a 13-bit SAR ADC with the proposed VCO-based comparator was fabricated in 65-nm CMOS. By off-chip LMS calibration, the ADC achieves peak SNDR 66 dB at 1 MS/s with a peak FoM of 29 fJ/conv.-step.

  • Access to Document (DOI)

• Through the Looking Glass: Diminishing Occlusions in Robot Vision Systems with Mirror Reflections

  Yoshioka K., Okuni H., Ta T.T., Sai A.

  IEEE International Conference on Intelligent Robots and Systems （IEEE International Conference on Intelligent Robots and Systems)     1578 - 1584 2021年

  ISSN  21530858

  　概要を見る

  The quality of robot vision greatly affects the performance of automation systems, where occlusions stand as one of the biggest challenges. If the target is occluded from the sensor, detecting and grasping such objects become very challenging. For example, when multiple robot arms cooperate in a single workplace, occlusions will be created under the robot arm itself and hide objects underneath. While occlusions can be greatly reduced by installing multiple sensors, the increase in sensor costs cannot be ignored. Moreover, the sensor placements must be rearranged every time the robot operation routine and layout change.To diminish occlusions, we propose the first robot vision system with tilt-type mirror reflection sensing. By instantly tilting the sensor itself, we obtain two sensing results with different views: conventional direct line-of-sight sensing and non-line-of-sight sensing via mirror reflections. Our proposed system removes occlusions adaptively by detecting the occlusions in the scene and dynamically configuring the sensor tilt angle to sense the detected occluded area. Thus, sensor rearrangements are not required even after changes in robot operation or layout. Since the required hardware is the tilt-unit and a commercially available mirror, the cost increase is marginal. Through experiments, we show that our system can achieve a similar detection accuracy as systems with multiple sensors, regardless of the single-sensor implementation.

  • Access to Document (DOI)

• System and method

  K Yoshioka, H Okuni, A Sai

  US Patent App. 17/014,757 2021年

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競争的研究費の研究課題 【 表示 ／ 非表示 】

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• サイバーとフィジカルを横断したセンサセキュリティ研究

  2022年10月

  -

  2026年03月

  JST, さきがけ, 受託研究,  研究代表者

• D3-AI: 多様性と環境変化に寄り添う分散機械学習基盤の創出

  2021年10月

  -

  2026年03月

  JST, CREST, 研究分担者

• LiDARを用いたプライバシーと死角に重点を置いた見守りセンシングシステムの構築

  2021年08月

  -

  2023年03月

  文部科学省・日本学術振興会, 科学研究費助成事業, 吉岡 健太郎, 研究活動スタート支援, 補助金,  研究代表者

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• Michael A. Zachariah Outstanding Student Paper Award

  K. Yamashita, B. Hershberg, K. Yoshioka, H. Ishikuro, 2023年04月, IEEE CICC, A 4.6K to 400K Functional PVT-Robust Ringamp-Based 250MS/s 12b Pipelined ADC with Pole-Aware Bias Calibration

  受賞区分： 国際学会・会議・シンポジウム等の賞,  受賞国： アメリカ合衆国

• ETAS Best Short/WIP Paper Award Runner-up

  T. Sato, Y.Hayakawa, R.Suzuki, Y.Shiiki, K.Yoshioka, Q. Chen, 2023年02月, Vehicle Sec, WIP: Practical Removal Attacks on LiDAR-based Object Detection in Autonomous Driving

  受賞区分： 国際学会・会議・シンポジウム等の賞,  受賞国： アメリカ合衆国

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• 理工学基礎実験

  2024年度

• 電気情報工学実験第１

  2024年度

• 総合デザイン工学課題研究

  2024年度

• 総合デザイン工学特別研究第２

  2024年度

• 総合デザイン工学特別研究第１

  2024年度

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学術貢献活動 【 表示 ／ 非表示 】

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• IEEE Symposium on VLSI Circuits Short Course Chair

  2022年01月

  -

  2023年12月

• IEEE Symposium on VLSI Circuits TPC Member

  2021年04月

  -

  継続中

• Symposium on Vehicle Security and Privacy TPC Member

  2023年01月

  -

  継続中

• IEEE Symposium on VLSI Circuits Short Course Organizer

  2021年04月

  -

  2021年12月

所属学協会 【 表示 ／ 非表示 】

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• IEEE, 

  2012年01月

  -

  継続中