Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
VLD, HWS, ICD |
2024-02-28 16:20 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Single Trunk Routing Problem for Generalized Channel Zezhong Wang, Masayuki Shimoda, Atsushi Takahashi (Tokyo Tech) VLD2023-104 HWS2023-64 ICD2023-93 |
This paper addresses the challenges posed by tight horizontal routing capacity in critical layers of chip design. A Gene... [more] |
VLD2023-104 HWS2023-64 ICD2023-93 pp.30-35 |
PN |
2021-03-02 14:30 |
Online |
Online |
RSA-RL: Reinforcement Learning Framework for Routing and Spectrum Assignment in Optical Networks Masayuki Shimoda, Takafumi Tanaka (NTT) PN2020-57 |
[more] |
PN2020-57 pp.88-91 |
IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] |
2020-01-22 17:20 |
Kanagawa |
Raiosha, Hiyoshi Campus, Keio University |
Many Universal Convolution Cores for Ensemble Sparse Convolutional Neural Networks Ryosuke Kuramochi, Youki Sada, Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (Titech) VLD2019-65 CPSY2019-63 RECONF2019-55 |
A convolutional neural network (CNN) is one of the most successful neural networks and widely used for computer vision t... [more] |
VLD2019-65 CPSY2019-63 RECONF2019-55 pp.67-72 |
IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] |
2020-01-22 17:45 |
Kanagawa |
Raiosha, Hiyoshi Campus, Keio University |
An FPGA Implementation of Monocular Depth Estimation Youki Sada, Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) VLD2019-66 CPSY2019-64 RECONF2019-56 |
Among a lot of image recognition applications, Convolutional Neural Network (CNN) has gained high accuracy and increasin... [more] |
VLD2019-66 CPSY2019-64 RECONF2019-56 pp.73-78 |
RECONF |
2019-09-20 11:40 |
Fukuoka |
KITAKYUSHU Convention Center |
Accurate Pedestrian Detection in Thermal Images for FPGA Ryosuke Kuramochi, Masayuki Shimoda, Youki Sada, Shimpei Sato, Hiroki Nakahara (titech) RECONF2019-26 |
Since thermal cameras can detect the heat of objects, they can be used even if there is no light.
Therefore, object de... [more] |
RECONF2019-26 pp.31-36 |
RECONF |
2019-05-10 10:00 |
Tokyo |
Tokyo Tech Front |
An FPGA Implementation of the Semantic Segmentation Model with Multi-path Structure Youki Sada, Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) RECONF2019-10 |
Since the convolutional neural network has a high-performance recognition accuracy,
it is expected to implement variou... [more] |
RECONF2019-10 pp.49-54 |
RECONF |
2019-05-10 15:30 |
Tokyo |
Tokyo Tech Front |
Spatial-Separable Convolution: Low memory CNN for FPGA Akira Jinguji, Masayuki Shimoda, Hiroki Nakahara (titech) RECONF2019-16 |
Object detection and image recognition using a Convolutional Neural Network (CNN) are used in em- bedded systems, which ... [more] |
RECONF2019-16 pp.85-90 |
HWS, VLD |
2019-02-27 10:25 |
Okinawa |
Okinawa Ken Seinen Kaikan |
FPGA Implementation of Fully Convolutional Network for Semantic Segmentation Masayuki Shimoda, Youki Sada, Hiroki Nakahara (titech) VLD2018-93 HWS2018-56 |
[more] |
VLD2018-93 HWS2018-56 pp.1-6 |
HWS, VLD |
2019-02-27 10:50 |
Okinawa |
Okinawa Ken Seinen Kaikan |
Spatial-Separable Convolution: Low memory CNN for FPGA Akira Jinguji, Masayuki Shimoda, Hiroki Nakahara (titech) VLD2018-94 HWS2018-57 |
Object detection and image recognition using a Convolutional Neural Network (CNN) are used in embedded systems, which re... [more] |
VLD2018-94 HWS2018-57 pp.7-12 |
IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] |
2019-01-30 13:55 |
Kanagawa |
Raiosha, Hiyoshi Campus, Keio University |
Filter-wise Pruning Approach to FPGA Implementation of Fully Convolutional Network for Semantic Segmentation Masayuki Shimoda, Youki Sada, Hiroki Nakahara (titech) VLD2018-76 CPSY2018-86 RECONF2018-50 |
[more] |
VLD2018-76 CPSY2018-86 RECONF2018-50 pp.25-30 |
VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2018-12-05 10:20 |
Hiroshima |
Satellite Campus Hiroshima |
An FPGA implementation of Tri-state YOLOv2 using Intel OpenCL Youki Sada, Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) RECONF2018-35 |
Since the convolutional neural network has a high-performance recognition accuracy,
it is expected to implement variou... [more] |
RECONF2018-35 pp.7-12 |
CPSY, DC, IPSJ-ARC (Joint) [detail] |
2018-08-01 17:00 |
Kumamoto |
Kumamoto City International Center |
A Deep Neuro-Fuzzy for False Negatives Reduction on an FPGA Masayuki Shimoda, Shimpei Sato, Nakahara Hiroki (titech) CPSY2018-29 |
[more] |
CPSY2018-29 pp.211-216 |
RECONF |
2018-05-25 16:00 |
Tokyo |
GATE CITY OHSAKI |
Efficient Object Detection with Event-Driven camera and its implementation on an FPGA Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) RECONF2018-17 |
We propose an object detection system using a sliding window method for an event-driven camera
which outputs a subtrac... [more] |
RECONF2018-17 pp.81-86 |
RECONF |
2018-05-25 16:25 |
Tokyo |
GATE CITY OHSAKI |
An Implementation of an Object Detector on an FPGA Hiroki Nakahara, Masayuki Shimoda, Shimpei Sato (Titech) RECONF2018-18 |
[more] |
RECONF2018-18 pp.87-92 |
IPSJ-ARC, VLD, CPSY, RECONF, IPSJ-SLDM [detail] |
2018-01-18 09:40 |
Kanagawa |
Raiosha, Hiyoshi Campus, Keio University |
All Binarized Conventional Neural Network and its Implementation on an FPGA
-- FPT2017 Design Competition Report -- Masayuki Shimoda, Shimpei Sato, Hiroki Nakahara (titech) VLD2017-63 CPSY2017-107 RECONF2017-51 |
[more] |
VLD2017-63 CPSY2017-107 RECONF2017-51 pp.7-11 |
RECONF |
2017-09-26 10:00 |
Tokyo |
DWANGO Co., Ltd. |
GUINNESS: A GUI based Binarized Deep Neural Network Framework for an FPGA Hiroki Nakahara, Haruyoshi Yonekawa, Tomoya Fujii, Masayuki Shimoda, Shimpei Sato (Tokyo Inst. of Tech.) RECONF2017-31 |
[more] |
RECONF2017-31 pp.51-56 |
CPSY, DC, IPSJ-ARC (Joint) [detail] |
2017-07-27 15:45 |
Akita |
Akita Atorion-Building (Akita) |
Consideration of All Binarized Convolutional Neural Network Masayuki Shimoda, Tomoya Fujii, Haruyoshi Yonekawa, Shimpei Sato, Hiroki Nakahara (Tokyo Inst. of Tech.) CPSY2017-28 |
A pre-trained convolutional neural network (CNN) is a feed-forward computation perspective, which is widely used for the... [more] |
CPSY2017-28 pp.131-136 |