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Teppei Suzuki
Teppei Suzuki
SB Intuitions
確認したメール アドレス: sbintuitions.co.jp - ホームページ
タイトル
引用先
引用先
TeachAugment: Data Augmentation Optimization Using Teacher Knowledge
T Suzuki
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
572022
Drive video analysis for the detection of traffic near-miss incidents
H Kataoka, T Suzuki, S Oikawa, Y Matsui, Y Satoh
2018 IEEE International Conference on Robotics and Automation (ICRA), 3421-3428, 2018
432018
Superpixel Segmentation Via Convolutional Neural Networks with Regularized Information Maximization
T Suzuki
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
272020
Changing fashion cultures
K Abe*, T Suzuki*, S Ueta, A Nakamura, Y Satoh, H Kataoka, ...
arXiv preprint arXiv:1703.07920, 2017
152017
Feature Space Particle Inference for Neural Network Ensembles
S Yashima, T Suzuki, K Ishikawa, I Sato, R Kawakami
Proceedings of the 39th International Conference on Machine Learning, 2022
132022
Adversarial Transformations for Semi-Supervised Learning
T Suzuki, I Sato
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5916-5923, 2020
132020
Clustering as attention: Unified image segmentation with hierarchical clustering
T Suzuki
arXiv preprint arXiv:2205.09949, 2022
12*2022
Pedestrian near-miss analysis on vehicle-mounted driving recorders
T Suzuki, Y Aoki, H Kataoka
2017 Fifteenth IAPR International Conference on Machine Vision Applications …, 2017
122017
Superpixel convolution for segmentation
T Suzuki, S Akizuki, N Kato, Y Aoki
2018 25th IEEE International Conference on Image Processing (ICIP), 3249-3253, 2018
112018
Fashion Culture Database: Construction of Database for World-wide Fashion Analysis
K Abe, M Minoguchi, T Suzuki, T Suzuki, N Akimoto, Y Qiu, R Suzuki, ...
2018 15th International Conference on Control, Automation, Robotics and …, 2018
82018
Federated Learning for Large-Scale Scene Modeling with Neural Radiance Fields
T Suzuki
arXiv preprint arXiv:2309.06030, 2023
62023
Tabulated MLP for Fast Point Feature Embedding
Y Sekikawa, T Suzuki
arXiv preprint arXiv:1912.00790, 2019
62019
Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning
T Suzuki
arXiv preprint arXiv:2403.11460, 2024
52024
Rethinking PointNet Embedding for Faster and Compact Model
T Suzuki, K Ozawa, Y Sekikawa
2020 International Conference on 3D Vision (3DV), 791-800, 2020
52020
QR-code Reconstruction from Event Data via Optimization in Code Subspace
J Nagata, Y Sekikawa, K Hara, T Suzuki, Y Aoki
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
52020
Joint Pedestrian Detection and Risk-level Prediction with Motion-Representation-by-Detection
H Kataoka, T Suzuki, K Nakashima, Y Satoh, Y Aoki
2020 IEEE International Conference on Robotics and Automation (ICRA), 1021-1027, 2020
42020
Does End-to-End Trained Deep Model Always Perform Better than Non-End-to-End Counterpart?
I Sato, G Liu, K Ishikawa, T Suzuki, M Tanaka
Electronic Imaging 2021 (10), 240-1-240-7, 2021
32021
cvpaper. challenge in 2016: futuristic computer vision through 1,600 papers survey
H Kataoka, S Shirakabe, Y He, S Ueta, T Suzuki, K Abe, A Kanezaki, ...
arXiv preprint arXiv:1707.06436, 2017
32017
Graph-text contrastive learning of inorganic crystal structure toward a foundation model of inorganic materials
K Ozawa, T Suzuki, S Tonogai, T Itakura
Science and Technology of Advanced Materials: Methods, 2406219, 2024
22024
Multi-task Curriculum Learning Based on Gradient Similarity
H Igarashi, K Yoneji, K Ishikawa, R Kawakami, T Suzuki, S Yashima, ...
The British Machine Vision Conference (BMVC), 2022
22022
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