Search Results for author: Takeaki Kadota

Found 3 papers, 0 papers with code

Deep Bayesian Active-Learning-to-Rank for Endoscopic Image Data

no code implementations5 Aug 2022 Takeaki Kadota, Hideaki Hayashi, Ryoma Bise, Kiyohito Tanaka, Seiichi Uchida

This paper proposes a deep Bayesian active-learning-to-rank, which trains a Bayesian convolutional neural network while automatically selecting appropriate pairs for relative annotation.

Active Learning Learning-To-Rank

Famous Companies Use More Letters in Logo:A Large-Scale Analysis of Text Area in Logo

no code implementations1 Apr 2021 Shintaro Nishi, Takeaki Kadota, Seiichi Uchida

Various findings include the weak positive correlation between the text area ratio and the number of followers of the company.

regression

Cannot find the paper you are looking for? You can Submit a new open access paper.