Maki Atsuto
Title
Cited by
Cited by
Year
A systematic study of the class imbalance problem in convolutional neural networks
M Buda, A Maki, MA Mazurowski
Neural Networks 106, 249-259, 2018
5912018
From generic to specific deep representations for visual recognition
H Azizpour, A Sharif Razavian, J Sullivan, A Maki, S Carlsson
Proceedings of the IEEE conference on computer vision and pattern …, 2015
3722015
Visual instance retrieval with deep convolutional networks
AS Razavian, J Sullivan, S Carlsson, A Maki
ITE Transactions on Media Technology and Applications 4 (3), 251-258, 2016
3322016
[Paper] Visual Instance Retrieval with Deep Convolutional Networks
AS Razavian, J Sullivan, S Carlsson, A Maki
ITE Transactions on Media Technology and Applications 4 (3), 251-258, 2016
3322016
Visual Instance Retrieval with Deep Convolutional Networks
A Sharif Razavian, J Sullivan, S Carlsson, A Maki
arXiv preprint arXiv:1412.6574, 2014
332*2014
Factors of transferability for a generic convnet representation
H Azizpour, AS Razavian, J Sullivan, A Maki, S Carlsson
IEEE transactions on pattern analysis and machine intelligence 38 (9), 1790-1802, 2016
2182016
Factors of transferability for a generic convnet representation
H Azizpour, AS Razavian, J Sullivan, A Maki, S Carlsson
IEEE transactions on pattern analysis and machine intelligence 38 (9), 1790-1802, 2016
2182016
Image processing apparatus and image processing method
A Maki, M Watanabe, N Matsuda, C Wiles
US Patent 6,072,903, 2000
1272000
Artificial intelligence for analyzing orthopedic trauma radiographs: deep learning algorithms—are they on par with humans for diagnosing fractures?
J Olczak, N Fahlberg, A Maki, AS Razavian, A Jilert, A Stark, ...
Acta orthopaedica 88 (6), 581-586, 2017
1182017
Towards a simulation driven stereo vision system
M Peris, A Maki, S Martull, Y Ohkawa, K Fukui
21st International Conference on Pattern Recognition, 2012
1092012
Attentional scene segmentation: integrating depth and motion
A Maki, P Nordlund, JO Eklundh
Computer Vision and Image Understanding 78 (3), 351-373, 2000
982000
Attentional scene segmentation: integrating depth and motion
A Maki, P Nordlund, JO Eklundh
Computer Vision and Image Understanding 78 (3), 351-373, 2000
982000
A computational model of depth-based attention
A Maki, P Nordlund, JO Eklundh
Proceedings of 13th International Conference on Pattern Recognition 4, 734-739, 1996
981996
Developing an active observer
JO Eklundh, T Uhlin, P Nordlund, A Maki
Recent Developments in Computer Vision, 181-190, 1996
83*1996
Difference sphere: an approach to near light source estimation
T Takai, A Maki, K Niinuma, T Matsuyama
Computer Vision and Image Understanding 113 (9), 966-978, 2009
802009
Difference sphere: an approach to near light source estimation
T Takai, K Niinuma, A Maki, T Matsuyama
IEEE Conference Computer Vision and Pattern Recognition, 2004
80*2004
Demisting the Hough transform for 3D shape recognition and registration
OJ Woodford, MT Pham, A Maki, F Perbet, B Stenger
International Journal of Computer Vision 106 (3), 332-341, 2014
772014
Demisting the Hough Transform
OJ Woodford, MT Pham, A Maki, F Perbet, B Stenger
77*
Deep predictive policy training using reinforcement learning
A Ghadirzadeh, A Maki, D Kragic, M Björkman
Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International …, 2017
712017
The multiple-camera 3-d production studio
J Starck, A Maki, S Nobuhara, A Hilton, T Matsuyama
IEEE Transactions on circuits and systems for video technology 19 (6), 856-869, 2009
692009
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