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All Technical Committee Conferences (Searched in: Recent 10 Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| PRMU, IPSJ-CVIM, VRSJ-SIG-MR, MVE | 2025-01-21 14:50 |
Fukuoka | (Fukuoka, Online) (Primary: On-site, Secondary: Online) |
Toward Explainable Recognition by Image Normalization Haruto Hirota, Koji Kamma, Toshikazu Wada (Wakayama Univ.)  PRMU2024-40 |
If the input image can be normalized to a class-specific pattern, inputs normalised to the same pattern are regarded bel... [more] | PRMU2024-40 pp.38-43 |
| PRMU, IPSJ-CVIM, VRSJ-SIG-MR, MVE | 2025-01-22 13:40 |
Fukuoka | (Fukuoka, Online) (Primary: On-site, Secondary: Online) |
Neighborhood sampling of training data and parameter adjustment method in DN4C Kizuki Yamada, Koji Kamma, Toshikazu Wada (Wakayama Univ) PRMU2024-44 |
DNN based image segmentation is widely used in various fields. However, DNN training requires training data and correspo... [more] | PRMU2024-44 pp.61-66 |
| PRMU, IPSJ-CVIM, IPSJ-CGVI, IPSJ-DCC | 2024-11-29 10:40 |
Fukui | (Fukui, Online) (Primary: On-site, Secondary: Online) |
Task Partitioning and Ordering for Continual Learning
-- Class Clustering from Confusion Matrix -- Toshikazu Wada (Wakayama Univ.) PRMU2024-8 |
“Continual learning” (also known as ‘class incremental learning’), in which a single model is trained while new classes ... [more] | PRMU2024-8 pp.1-6 |
| PRMU, IPSJ-CVIM, IPSJ-CGVI, IPSJ-DCC | 2024-11-30 10:15 |
Fukui | (Fukui, Online) (Primary: On-site, Secondary: Online) |
Disentangle Learning for Interactive Semiconductor Inspection Robust to Thin-Film Interference Koki Mitsusada, Koji Kamma, Toshikazu Wada (Wakayama Univ.), Yasuhiro Hamada, Yoshinori Shimada, Takeshi Noguchi, Toshiyuki Okayama (Advanced System Solutions Co., Ltd.) PRMU2024-25 |
In the semiconductor wafer inspection process, an intensity difference-based method is widely used, in which defects are... [more] | PRMU2024-25 pp.93-98 |
| PRMU, IBISML, IPSJ-CVIM | 2024-03-04 15:30 |
Hiroshima | Hiroshima Univ. Higashi-Hiroshima campus (Hiroshima, Online) (Primary: On-site, Secondary: Online) |
Development of a Method of Growth Diagnosis for Mini-tomatoes Using a Color Stereo Camera Hiroki Egawa (Wakayama Univ.), Toshiya Tanaka, Hiromi Hanada (Warm Place Gardening Center), Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2023-74 |
(To be available after the conference date) [more] | PRMU2023-74 pp.134-139 |
| PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM | 2024-01-25 13:30 |
Kanagawa | Keio Univ. (Hiyoshi Campus) (Kanagawa) | [Fellow Memorial Lecture]
Hypothesis Generation and Verification/Refinement
-- Messages embedded in my research -- Toshikazu Wada (Wakayama Univ.) PRMU2023-41 |
[more] | PRMU2023-41 p.13 |
| PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI | 2023-11-17 14:40 |
Tottori | (Tottori, Online) (Primary: On-site, Secondary: Online) |
A context-dependent character sequence recognition based on ambiguous recognition expression Shu Kimoto, Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2023-37 |
Classification is usually regarded as a task of determining the class to which a given input belongs, however, the class... [more] | PRMU2023-37 pp.119-124 |
| PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI | 2023-11-17 14:40 |
Tottori | (Tottori, Online) (Primary: On-site, Secondary: Online) |
An image based barcode reading using Hough transform and 1-D super resolution Hiroki Egawa, Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2023-38 |
There is a demand for automatic reading of shelf tag barcodes captured by mobile robots to assist shelf allocation. In t... [more] | PRMU2023-38 pp.125-130 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 09:40 |
Hokkaido | Future University Hakodate (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Pruning for Producing Efficient DNNs: Neuron Selection and Reconstruction based on Final Layer Error Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2022-66 IBISML2022-73 |
Deep Neural Networks (DNNs) are dominant in the field of machine learning. However, because DNN models have large comput... [more] | PRMU2022-66 IBISML2022-73 pp.42-47 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 17:30 |
Hokkaido | Future University Hakodate (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
A Study on Data Augmentation by Pixel Value Transformation for Product Image Retrieval DNN Yu Okamoto, Masaki Kishibe, Toshikazu Wada (Wakayama Univ.) PRMU2022-94 IBISML2022-101 |
We are developing a product image retrieval DNN for supporting shelving allocation tasks. To train the DNN, product imag... [more] | PRMU2022-94 IBISML2022-101 pp.181-186 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-03 17:00 |
Hokkaido | Future University Hakodate (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Continual learning combining Replay and Parameter Isolation Methods Ryota Adachi, Toshikazu Wada (Wakayama Univ.) PRMU2022-121 IBISML2022-128 |
Deep Neural Networks (DNN) are used for various tasks such as image classification, but when a new task is trained on a ... [more] | PRMU2022-121 IBISML2022-128 pp.335-340 |
| PRMU | 2022-12-15 10:45 |
Toyama | Toyama International Conference Center (Toyama, Online) (Primary: On-site, Secondary: Online) |
DN4C
-- An Interactive Image Segmentation System Combining Deep Neural Network and Nearest Neighbor Classifier -- Toshikazu Wada, Koji Kamma (Wakayama University) PRMU2022-35 |
Color/texture based image segmentation can be widely applied to the images for product and/or medical inspection, remote... [more] | PRMU2022-35 pp.19-24 |
| PRMU | 2022-12-15 14:25 |
Toyama | Toyama International Conference Center (Toyama, Online) (Primary: On-site, Secondary: Online) |
A DNN compression method based on output error of activation functions Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2022-38 |
Deep Neural Networks (DNNs) are dominant in the field of machine learning. However, because DNN models have large comput... [more] | PRMU2022-38 pp.34-39 |
| PRMU | 2022-12-16 10:00 |
Toyama | Toyama International Conference Center (Toyama, Online) (Primary: On-site, Secondary: Online) |
Image Transformation Simulating the Height Change of Wide-angle Ceiling Camera for People Detection Hayato Kitao, Toshikazu Wada (Wakayama Univ.) PRMU2022-43 |
In recent years, surveillance cameras have been widely installed inside the buildings. Especially, wide-angle ceiling ca... [more] | PRMU2022-43 pp.57-62 |
| PRMU | 2022-12-16 14:10 |
Toyama | Toyama International Conference Center (Toyama, Online) (Primary: On-site, Secondary: Online) |
Sampling Strategies in Data Pruning Ryota Higashi, Toshikazu Wada (Wakayama Univ.) PRMU2022-48 |
Data Pruning is a method of selecting the training data out of an entire training dataset so as to keep the accuracy aft... [more] | PRMU2022-48 pp.85-90 |
| PRMU | 2022-09-14 15:45 |
Kanagawa | (Kanagawa, Online) (Primary: On-site, Secondary: Online) |
Human Pose Transfer with Reduced Color Transfer by Occlusion for Person Re-Identification Masaki Kishibe, Toshikazu Wada (Wakayama Univ.) PRMU2022-15 |
Human pose transfer is the task that transforms a person image from the source pose to a given target pose, and is usefu... [more] | PRMU2022-15 pp.31-36 |
| PRMU | 2022-09-14 16:00 |
Kanagawa | (Kanagawa, Online) (Primary: On-site, Secondary: Online) |
Convolutional Skip Connection for Compressing DNNs with Branched Architectures Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2022-16 |
Although Deep Neural Network (DNN) is a core technology in Computer Vision, it is difficult to implement DNN models beca... [more] | PRMU2022-16 pp.37-42 |
| PRMU | 2021-12-16 16:30 |
Online | Online (Online) | Recurrent Tracknet : Continuous ball detection using Deep Neural Network Gen Maesako, Toshikazu Wada (Wakayama Univ.) PRMU2021-38 |
[more] | PRMU2021-38 pp.77-82 |
| PRMU | 2021-12-16 16:30 |
Online | Online (Online) | Examination of facial pattern structure estimation using GCN Naoya Maruoka, Toshikazu Wada (Wkayama Univ.) PRMU2021-41 |
[more] | PRMU2021-41 pp.92-97 |
| PRMU | 2021-12-17 14:45 |
Online | Online (Online) | Data Selection for Efficient Deep Learning Ryota Higashi, Toshikazu Wada (Wakayama Univ.) PRMU2021-51 |
We are investigating the method to sample the important data from the whole dataset for efficient training of Deep Neura... [more] | PRMU2021-51 pp.148-153 |
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