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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 125  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
AP 2024-03-15
10:25
Fukui UNIVERSITY OF FUKUI
(Primary: On-site, Secondary: Online)
A Study on Path loss characteristics estimation methods considering geographical conditions for designing narrowband DR-IoT communication system
Takato Ikegame, Naoki Ikeda, Motonari Imai, Tetsushi Ikegami (Meiji Univ.), Mineo Takai (Osaka Univ.), Susumu Ishihara (Shizuoka Univ.), Arata Kato, Shugo Kajita (STE)
(To be available after the conference date) [more]
DC 2024-02-28
13:40
Tokyo Kikai-Shinko-Kaikan Bldg. Test Point Selection Method for Multi-Cycle BIST Using Deep Reinforcement Learning
Kohei Shiotani, Tatsuya Nishikawa, Shaoqi Wei, Senling Wang, Hiroshi Kai, Yoshinobu Higami, Hiroshi Takahashi (Ehime Univ.) DC2023-98
(To be available after the conference date) [more] DC2023-98
pp.23-28
PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM 2024-01-26
15:46
Kanagawa Keio Univ. (Hiyoshi Campus) PRMU2023-48 In the realm of autonomous driving, end-to-end models (E2EDMs) have gained prominence due to their high predictive accur... [more] PRMU2023-48
pp.46-49
ICTSSL, CAS 2024-01-25
11:45
Kanagawa
(Primary: On-site, Secondary: Online)
Comparison of transfer learning and fine tuning
Ohata Shunsuke, Okazaki Hideaki (SIT) CAS2023-88 ICTSSL2023-41
This report examines the principal image recognition methods. First, we show the experimental results of image recogniti... [more] CAS2023-88 ICTSSL2023-41
pp.31-33
NC, MBE, NLP, MICT
(Joint) [detail]
2024-01-25
09:00
Tokushima Naruto University of Education The Relationship Between Metrics in the Latent Variable Space and Image Classification Performance
Haruki Wakasa, Kenya Jin'no (Tokyo City Univ.) NLP2023-99 MICT2023-54 MBE2023-45
In recent years, models based on convolutional neural networks (CNNs) have exhibited high performance in image classific... [more] NLP2023-99 MICT2023-54 MBE2023-45
pp.78-81
SeMI 2024-01-18
13:30
Yamanashi Raki House Kaiji Enhancing Human Skeleton Estimation with Multi-Frame mmWave Radar Point Cloud-based Method
Xintong Shi, Tomoaki Ohtsuki (Keio Univ.) SeMI2023-52
Millimeter-Wave (mmWave) radar-based skeleton estimation has emerged as a focal point in the realm of human motion analy... [more] SeMI2023-52
pp.18-21
NLP 2023-11-28
13:50
Okinawa Nago city commerce and industry association Considerations on the distribution of latent variables in CNNs
Mizuki Dai, Kenya Jin'no (Tokyo City Univ.) NLP2023-65
Abstract Fully comprehending the output decision mechanisms of neural networks is a critical challenge. This article foc... [more] NLP2023-65
pp.31-34
SCE 2023-10-31
10:00
Miyagi RIEC, Tohoku Univ.
(Primary: On-site, Secondary: Online)
Design of a Modularized Circuits Library for Binary Convolutional Neural Network Accelerator using Single Flux Quantum Circuits
Zeyu Han, Zongyuan Li, Yuki Yamanashi, Nobuyuki Yoshikawa (Yokohama National Univ.) SCE2023-17
To implement a binary neural network (BNN) based on SFQ circuits, we designed a modularized circuits library based on th... [more] SCE2023-17
pp.26-31
BioX 2023-10-12
15:25
Okinawa Nobumoto Ohama Memorial Hall A Study on Ear Acoustic Personal Authentication System Using Domain Transformation for Numerical Analysis Data
Masafumi Morimoto (Kansai Univ.), Shunsuke Kita (ORIST), Yoshinobu Kajikawa (Kansai Univ.) BioX2023-60
We propose a new personal authentication system using ear pinna transfer functions.
This proposed method is constructe... [more]
BioX2023-60
pp.12-15
EMCJ, IEE-EMC, IEE-SPC 2023-05-12
13:15
Okinawa  
(Primary: On-site, Secondary: Online)
Evaluating Transmission Efficiency Impact on Screen Reconstruction Accuracy for High-Resolution Displays
Taiki Kitazawa, Yuichi Hayashi (NAIST) EMCJ2023-6
In TEMPEST attacks targeting high-resolution displays with divided screens, reconstructing screen information proves dif... [more] EMCJ2023-6
pp.1-6
NLP, MSS 2023-03-17
16:05
Nagasaki
(Primary: On-site, Secondary: Online)
Lightweighting Noisy Student Semi-Supervised Learning by Applying MobileNet
Yuga Morishima, Hidehiro Nakano (Tokyo City Univ.) MSS2022-108 NLP2022-153
Recently, Convolutional Neural Networks (CNNs) have attracted much attention in various fields such as image classificat... [more] MSS2022-108 NLP2022-153
pp.220-224
MI 2023-03-06
13:15
Okinawa OKINAWA SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Improvement of Small Organ Accuracy in Multi-Organ Segmentation of Abdominal CT Images Using 2.5D Deformable Convolutional CNN
Yuya Okumura, Hiroyuki Kudo, Hotaka Takizawa (Univ of Tsukuba) MI2022-80
In multi-organ segmentation of abdominal CT images using deep learning, small organs such as the pancreas are difficult ... [more] MI2022-80
pp.38-39
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-02
11:15
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
Dynamic Weight Scheduling for Long-tailed Visual Recognition
Xinyuan Li (Ritsumeikan Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Ritsumeikan Univ.) PRMU2022-78 IBISML2022-85
For long-tailed image recognition tasks, re-weighting is effective to alleviate data imbalance by assigning higher weigh... [more] PRMU2022-78 IBISML2022-85
pp.107-110
CAS, CS 2023-03-01
09:30
Fukuoka Kitakyushu International Conference Center
(Primary: On-site, Secondary: Online)
Modification and Comparison of Learning Sudoku with Convolutional Networks
Koichiro Ishii, Hiroshi Tamura (Chuo Univ.) CAS2022-96 CS2022-73
Sudoku is a logic puzzle in which the number between 1 and 9 is to fill in the boxes of the 9x9 grid by using the number... [more] CAS2022-96 CS2022-73
pp.1-5
ICTSSL, CAS 2023-01-26
11:15
Tokyo TBD
(Primary: On-site, Secondary: Online)
On Image Recognition Neural Networks and Polynomial Approximation of Images
Jiahang Chang, Kazuya Ozawa, Hideaki Okazaki (SIT) CAS2022-66 ICTSSL2022-30
In this report, we present a convolutional neural network that we have built ourselves for our research. Then, we discus... [more] CAS2022-66 ICTSSL2022-30
pp.23-27
IBISML 2022-12-23
11:10
Kyoto Kyoto University
(Primary: On-site, Secondary: Online)
Enhancement of Audio Signals Using Learning from Positive and Unlabelled Data
Nobutaka Ito, Masashi Sugiyama (UTokyo) IBISML2022-56
Audio signal enhancement (SE) is the task of extracting a desired class of sounds (a “signal”) from an observed sound mi... [more] IBISML2022-56
pp.94-100
HCGSYMPO
(2nd)
2022-12-14
- 2022-12-16
Kagawa Onsite (Sunport Takamatsu) and Online
(Primary: On-site, Secondary: Online)
Analyzing and Recognizing Synergetic Functions between Head Movements and Facial Expressions in Conversations
Mai Imamura, Kazuki Takeda (YNU), Shiro Kumano (NTT), Kazuhiro Otsuka (YNU)
In this paper, we propose machine-learning models for recognizing the synergetic functions between facial expressions an... [more]
MBE, NC 2022-12-03
11:00
Osaka Osaka Electro-Communication University Image Classification Using Gabor Filters as Preprocessing for CNNs
Akito Morita, Hirotsugu Okuno (OIT) MBE2022-32 NC2022-54
Image preprocessing is a promising approach to improve accuracy in image classification using convolutional neural netwo... [more] MBE2022-32 NC2022-54
pp.43-46
CCS, NLP 2022-06-09
14:15
Osaka
(Primary: On-site, Secondary: Online)
Improvement of Recognition Accuracy by Sequential Execution of Unsupervised Learning and Semi-supervised Learning
Hiroki Murakami, Hidehiro Nakano (Tokyo City Univ.) NLP2022-4 CCS2022-4
In this study, we propose a sequential learning method that improves recognition accuracy by alternately utilizing the k... [more] NLP2022-4 CCS2022-4
pp.17-22
CCS, NLP 2022-06-09
14:55
Osaka
(Primary: On-site, Secondary: Online)
Basic Performance of CNNs Using Dynamic Filters Based on Octave Convolution
Kiyotaka Matono, Hidehiro Nakano (Tokyo City Univ.) NLP2022-5 CCS2022-5
The methods of using dynamic filters for convolutional neural networks (CNNs) have attracted attentions. In recent years... [more] NLP2022-5 CCS2022-5
pp.23-26
 Results 1 - 20 of 125  /  [Next]  
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