Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Shinya Ohtani"'
Publikováno v:
IEICE Transactions on Information and Systems. (1):183-193
This paper presents an image super-resolution technique using a convolutional neural network (CNN) and multi-task learning for multiple image categories. The image categories include natural, manga, and text images. Their features differ from each ot
Publikováno v:
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. (7):955-958
Convolutional neural network (CNN)-based image super-resolutions are widely used as a high-quality image-enhancement technique. However, in general, they show little to no luminance isotropy. Thus, we propose two methods, “Luminance Inversion Train
Publikováno v:
IEEJ Transactions on Electronics, Information and Systems. 140:638-650
Publikováno v:
IEEJ Transactions on Electronics, Information and Systems. 138:957-963
Publikováno v:
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. (2):572-580
This paper proposes image super-resolution techniques with multi-channel convolutional neural networks. In the proposed method, output pixels are classified into KxK groups depending on their coordinates. Those groups are generated from separate chan
Publikováno v:
NEWCAS
This paper proposes image super-resolution techniques with multi-channel convolutional neural networks (CNN). In the proposed method, output pixels are classified into four groups depending on their positions. Those groups are generated from separate
Autor:
Shinya Ohtani, Fumito Koike
Publikováno v:
Applied Vegetation Science. 8:125-132
Autor:
Shinya Ohtani, Fumito Koike
Publikováno v:
Applied Vegetation Science. 8:125
Questions: What is the effect of the 19th century (pre-industrialization) landscape pattern on the recovery of climax forests in cool-temperate mountain areas dominated by Fagus crenata (Japanese beech)? Location: Secondary forests on Mt. Daisen, wes