フォロー
Masanori Suganuma
Masanori Suganuma
確認したメール アドレス: vision.is.tohoku.ac.jp - ホームページ
タイトル
引用先
引用先
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures
M Suganuma, S Shirakawa, T Nagao
Proceedings of the Genetic and Evolutionary Computation Conference 2017, 497-504, 2017
6932017
Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
X Liu, M Suganuma, Z Sun, T Okatani
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
2032019
Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
M Suganuma, M Ozay, T Okatani
International Conference on Machine Learning (ICML), 2018
1002018
Attention-based adaptive selection of operations for image restoration in the presence of unknown combined distortions
M Suganuma, X Liu, T Okatani
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
932019
Evolution of deep convolutional neural networks using cartesian genetic programming
M Suganuma, M Kobayashi, S Shirakawa, T Nagao
Evolutionary computation 28 (1), 141-163, 2020
682020
GRIT: Faster and Better Image captioning Transformer Using Dual Visual Features
VQ Nguyen, M Suganuma, T Okatani
arXiv:2207.09666 (Accepted to ECCV'22), 2022
472022
Hyperparameter-Free Out-of-Distribution Detection Using Cosine Similarity
E Techapanurak, M Suganuma, T Okatani
Proceedings of the Asian Conference on Computer Vision (ACCV), 2020
422020
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs
VQ Nguyen, M Suganuma, T Okatani
European Conference on Computer Vision (ECCV), 2020
332020
Hyperparameter-free out-of-distribution detection using softmax of scaled cosine similarity
E Techapanurak, M Suganuma, T Okatani
arXiv:1905.10628 (Accepted to ACCV), 2019
252019
Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following Tasks
VQ Nguyen, M Suganuma, T Okatani
arXiv preprint arXiv:2106.00596 (IJCAI 2021), 2021
212021
Hierarchical feature construction for image classification using genetic programming
M Suganuma, D Tsuchiya, S Shirakawa, T Nagao
IEEE International Conference on Systems, Man, and Cybernetics (SMC), 001423 …, 2016
152016
Matching in the Dark: A Dataset for Matching Image Pairs of Low-light Scenes
W Song, M Suganuma, X Liu, N Shimobayashi, D Maruta, T Okatani
IEEE International Conference on Computer Vision (ICCV), 6029-6038, 2021
122021
How can CNNs use image position for segmentation?
R Murase, M Suganuma, T Okatani
arXiv preprint arXiv:2005.03463, 2020
122020
Designing convolutional neural network architectures using cartesian genetic programming
M Suganuma, S Shirakawa, T Nagao
Deep Neural Evolution: Deep Learning with Evolutionary Computation, 185-208, 2020
112020
Cross-region domain adaptation for class-level alignment
Z Wang, X Liu, M Suganuma, T Okatani
arXiv preprint arXiv:2109.06422, 2021
92021
k‐Means Clustering for Prediction of Tensile Properties in Carbon Fiber‐Reinforced Polymer Composites
H Kurita, M Suganuma, Y Wang, F Narita
Advanced Engineering Materials 24 (5), 2101072, 2022
82022
Removal of Image Obstacles for Vehicle-Mounted Surrounding Monitoring Cameras by Real-Time Video Inpainting
Y Hirohashi, K Narioka, M Suganuma, X Liu, Y Tamatsu, T Okatani
IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW …, 2020
72020
Restoring images with unknown degradation factors by recurrent use of a multi-branch network
X Liu, M Suganuma, X Luo, T Okatani
arXiv preprint arXiv:1907.04508, 2019
6*2019
Efficient attention mechanism for handling all the interactions between many inputs with application to visual dialog
VQ Nguyen, M Suganuma, T Okatani
arXiv:1911.11390 (European Conference on Computer Vision (ECCV)), 2019
52019
Analysis and a Solution of Momentarily Missed Detection for Anchor-based Object Detectors
Y Hosoya, M Suganuma, T Okatani
WACV 2020, 2019
42019
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