1.5k citations · 2.1k across the 52 of their papers we have counts for
6 papers · 1 filter
Unpaired Image Enhancement Featuring Reinforcement-Learning-Controlled Image Editing Software
Satoshi Kosugi, Toshihiko Yamasaki
This paper tackles unpaired image enhancement, a task of learning a mapping function which transforms input images into enhanced images in the absence of input-output image pairs.…
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image Processing
Ryosuke Furuta, Naoto Inoue, Toshihiko Yamasaki
This paper tackles a new problem setting: reinforcement learning with pixel-wise rewards (pixelRL) for image processing. After the introduction of the deep Q-network, deep RL has b…
User-Aware Folk Popularity Rank: User-Popularity-Based Tag Recommendation That Can Enhance Social Popularity
Xueting Wang, Yiwei Zhang, Toshihiko Yamasaki
In this paper we propose a method that can enhance the social popularity of a post (i.e., the number of views or likes) by recommending appropriate hash tags considering both conte…
Object-Aware Instance Labeling for Weakly Supervised Object Detection
Satoshi Kosugi, Toshihiko Yamasaki, Kiyoharu Aizawa
Weakly supervised object detection (WSOD), where a detector is trained with only image-level annotations, is attracting more and more attention. As a method to obtain a well-perfor…
Lunar surface image restoration using U-net based deep neural networks
Hiya Roy, Subhajit Chaudhury, Toshihiko Yamasaki +3
Image restoration is a technique that reconstructs a feasible estimate of the original image from the noisy observation. In this paper, we present a U-Net based deep neural network…
Improving image classifiers for small datasets by learning rate adaptations
Sourav Mishra, Toshihiko Yamasaki, Hideaki Imaizumi
Our paper introduces an efficient combination of established techniques to improve classifier performance, in terms of accuracy and training time. We achieve two-fold to ten-fold s…