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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 27件中 1~20件目  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
EMM, IT 2019-05-23
14:00
Hokkaido Asahikawa International Conference Hall Generation of privacy-preserving images holding positional information for HOG feature extraction
Masaki Kitayama, Hitoshi Kiya (Tokyo Metro. Univ.) IT2019-1 EMM2019-1
In this paper, we propose a generation method of images which have no visual information but hold the gradient direction... [more] IT2019-1 EMM2019-1
pp.1-6
ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] 2019-02-20
09:30
Hokkaido Hokkaido Univ. Detection of Improper Tactile Paving using Pedestrian Viewpoint video
Kento Watanabe, Hiroki Takahashi (UEC) ITS2018-73 IE2018-94
Currently, there are 36 million blind people in the whole world. Furthermore, the number of blind people will be expecte... [more] ITS2018-73 IE2018-94
pp.141-146
VLD, HWS
(Joint)
2018-03-01
09:25
Okinawa Okinawa Seinen Kaikan Efficient Generation of Lithography Hotspot Detector based on Transfer Learning
Shuhei Suzuki, Yoichi Tomioka (UoA) VLD2017-106
As semiconductor features shrink in size, the fidelity of the layout pattern transferred onto the wafer decreases. A layo... [more] VLD2017-106
pp.103-108
PRMU, IPSJ-CVIM, MVE [detail] 2017-01-20
15:35
Kyoto   Cooking Gesture Recognition based on Spatio-Temporal Histogram of Oriented Gradient Features
Seiji Kojima, Wataru Ohyama, Tetsushi Wakabayashi (Mie Univ.) PRMU2016-145 MVE2016-36
In this research, we propose a cooking gesture recognition method.
The outline of this research is as follows,
(1) Act... [more]
PRMU2016-145 MVE2016-36
pp.315-319
VLD, DC, CPSY, RECONF, CPM, ICD, IE
(Joint) [detail]
2016-11-29
10:30
Osaka Ritsumeikan University, Osaka Ibaraki Campus Accurate Lithography Simulation Model based on Deep Learning
Yuki Watanabe, Tetsuaki Matsunawa, Taiki Kimura, Shigeki Nojima (Toshiba) VLD2016-56 DC2016-50
Lithography simulation is an indispensable technology for today's semiconductor manufacturing processes. To achieve accu... [more] VLD2016-56 DC2016-50
pp.73-78
VLD 2016-03-02
10:55
Okinawa Okinawa Seinen Kaikan Lithography Hotspot Detection Using Histogram of Oriented Light Propagation
Yoichi Tomioka (UoA), Tetsuaki Matsunawa (Toshiba) VLD2015-136
In recent semiconductor manufacturing process, it is essential to detect and to remove lithography hotspots, which induc... [more] VLD2015-136
pp.143-148
ITS, IE, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] 2016-02-23
12:00
Hokkaido Hokkaido Univ. Consideration of Frame Image Selection and Size for Detection System of Unusual Situation
Sachi Kuranishi, Hitoshi Yamauchi, Hironori Takimoto (Okayama Pref. Univ.) ITS2015-81 IE2015-123
We proposed an unusual situation detection system with camera used for elderly living alone. As the system's first step... [more] ITS2015-81 IE2015-123
pp.269-274
VLD, DC, IPSJ-SLDM, CPSY, RECONF, ICD, CPM
(Joint) [detail]
2015-12-03
10:10
Nagasaki Nagasaki Kinro Fukushi Kaikan High-level synthesis of an image-based human detection FPGA system with a machine learning technique
Ryo Fujita, Masahito Oishi, Yoshiki Hayashida, Yuichiro Shibata, Kiyoshi Oguri (Nagasaki Univ.) RECONF2015-58
In this paper, we discuss an FPGA implementation of image-based human detection system using histograms of oriented grad... [more] RECONF2015-58
pp.57-62
ICD, IE, VLD, IPSJ-SLDM [detail] 2015-10-27
09:50
Miyagi   [Invited Talk] Developments of Advanced Driver Assistance System (ADAS) and Image Recognition SoC
Takashi Miyamori (Toshiba), Seiya Ide (DENSO) VLD2015-34 ICD2015-47 IE2015-69
Recent years, Advanced Driver Assistance Systems, ADAS, such as an autonomous emergency braking for vehicles and pedestr... [more] VLD2015-34 ICD2015-47 IE2015-69
p.43
AP 2015-10-22
09:55
Yamaguchi Yamaguchi Pref. Roufukukyo-kaikan Double layered Loop-Slot Type FSS with Orthogonal Polarization Conversion Function
Shiro Handa, Ryuji Kuse, Toshikazu Hori, Mitoshi Fujimoto (Univ.Fukui) AP2015-93
FSS(Frequency Selective Surface) is a surface which pass or reject electromagnetic wave at a specific frequency. It is r... [more] AP2015-93
pp.5-8
VLD, DC, IPSJ-SLDM, CPSY, RECONF, ICD, CPM
(Joint) [detail]
2014-11-26
11:35
Oita B-ConPlaza Efficient FPGA resource allocation for HOG-based human detection
Masahito Oishi, Yuichiro Shibata, Kiyoshi Oguri (Nagasaki Univ.) RECONF2014-39
In this paper, we discuss implementation for highly efficient and compact FPGA implementation of an image-based
real-ti... [more]
RECONF2014-39
pp.31-36
ICD 2012-12-17
15:55
Tokyo Tokyo Tech Front [Poster Presentation] FPGA Implementation of HOG-based Real-Time Object Detection Processor
Kenta Takagi, Kosuke Mizuno, Shintaro Izumi, Hiroshi Kawaguchi, Masahiko Yoshimoto (Kobe Univ.) ICD2012-105
Histogram of Oriented Gradients (HOG) is widely accepted feature descriptor for object detection. HOG is robust against ... [more] ICD2012-105
p.61
AP, RCS
(Joint)
2012-11-15
11:00
Tokyo Tokyo Denki University [Tutorial Lecture] OFDM Transmission in Multi-path Propagation Environment
Mitoshi Fujimoto (Univ. of Fukui) AP2012-97 RCS2012-164
The OFDM Transmission has been introduced in many mobile communication systems because it has the features of high frequ... [more] AP2012-97 RCS2012-164
pp.25-30(AP), pp.19-24(RCS)
NC 2012-10-04
10:20
Fukuoka Kyushu Institute of Technology (Wakamatsu Campus) Comparison of Normalization Methods for Image Features Employed in Human Detection by Shape-Based Features
Shohei Iwamoto, Akitoshi Hanazawa (KIT) NC2012-36
In this paper, we compare the efficiency of normalization process for HOG features. HOG feature is one of shape-based fe... [more] NC2012-36
pp.1-6
PRMU, FM 2011-12-15
09:30
Shizuoka Hamamatsu Campus, Shizuoka Univ. A study on spatio-temporal CoHOG features for recognition of generic objects in video
Shogo Nakamura, Daisuke Deguchi (Nagoya Univ.), Tomokazu Takahashi (Gifu Shotoku Gakuen Univ.), Ichiro Ide, Hiroshi Murase (Nagoya Univ.) PRMU2011-124
Recognizing objects in videos is one of the important technologies to search a large amount of videos efficiently on the... [more] PRMU2011-124
pp.1-6
NC 2011-10-20
09:30
Fukuoka Ohashi Campus, Kyushu Univ. Introduction of Spatial Limitation to Human Detection by Co-occurrence with Shape and Color Self-Similarity Features
Hironori Matsui, Akitoshi Hanazawa (Kyutech) NC2011-59
In this paper, we propose a method for human detection with a spatial limitation introduced to the co-occurrence algorit... [more] NC2011-59
pp.83-88
RECONF, VLD, CPSY, IPSJ-SLDM [detail] 2011-01-18
09:40
Kanagawa Keio Univ (Hiyoshi Campus) FPGA implementation of human detectin with HOG features and AdaBoost
Kazuhiro Negi, Keisuke Dohi, Yuichiro Shibata, Kiyoshi Oguri (Nagasaki Univ.) VLD2010-100 CPSY2010-55 RECONF2010-69
An increase in in-home accidental deaths of elderly person caused by
falling and fainting, which are nonfatal if detect... [more]
VLD2010-100 CPSY2010-55 RECONF2010-69
pp.117-122
HIP, HCS 2010-05-14
15:20
Okinawa Okinawa Industry Support Center Generic Object Recognition with multiple Local features for Information Presentation system
Satoru Odo (Okinawa Univ.) HCS2010-22 HIP2010-22
This is to propose the information display system aimed at applications to the welfare field such as memory compensation... [more] HCS2010-22 HIP2010-22
pp.121-123
PRMU, HIP 2010-03-16
14:25
Kagoshima Kagoshima Univ. Recognition of specific specific behaviors in crowded video sequences based on human trajectory
Masaki Takahashi, Mahito Fujii, Masahiro Shibata (NHK), Shin'ichi Satoh (NII) PRMU2009-304 HIP2009-189
We describe a method that can detect specific human behaviors even in crowded surveillance video scenes. Our proposed me... [more] PRMU2009-304 HIP2009-189
pp.419-424
PRMU, HIP 2010-03-16
15:05
Kagoshima Kagoshima Univ. Hand Shape Recognition based on SVM and online learning with HOG
Ryousuke Mutou, Kazutaka Shimada, Tsutomu Endo (Kyushu Inst. of Tech.) PRMU2009-311 HIP2009-196
In this paper, we proposed a combined method for hand shape recognition. It consists of support vector machines (SVMs) a... [more] PRMU2009-311 HIP2009-196
pp.459-464
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