7 papers
Feedback is Needed for Retakes: An Explainable Poor Image Notification Framework for the Visually Impaired
Kazuya Ohata, Shunsuke Kitada, Hitoshi Iyatomi
We propose a simple yet effective image captioning framework that can determine the quality of an image and notify the user of the reasons for any flaws in the image. Our framework…
Ad Creative Discontinuation Prediction with Multi-Modal Multi-Task Neural Survival Networks
Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki
Discontinuing ad creatives at an appropriate time is one of the most important ad operations that can have a significant impact on sales. Such operational support for ineffective a…
Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation
Takumi Aoki, Shunsuke Kitada, Hitoshi Iyatomi
We propose a new character-based text classification framework for non-alphabetic languages, such as Chinese and Japanese. Our framework consists of a variational character encoder…
AraDIC: Arabic Document Classification using Image-Based Character Embeddings and Class-Balanced Loss
Mahmoud Daif, Shunsuke Kitada, Hitoshi Iyatomi
Classical and some deep learning techniques for Arabic text classification often depend on complex morphological analysis, word segmentation, and hand-crafted feature engineering.…
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative
Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki
Accurately predicting conversions in advertisements is generally a challenging task, because such conversions do not occur frequently. In this paper, we propose a new framework to…
End-to-End Text Classification via Image-based Embedding using Character-level Networks
Shunsuke Kitada, Ryunosuke Kotani, Hitoshi Iyatomi
For analysing and/or understanding languages having no word boundaries based on morphological analysis such as Japanese, Chinese, and Thai, it is desirable to perform appropriate w…