16 citations · 25 across the 11 of their papers we have counts for
11 papers
GenGA: Editable and Data-Grounded Graphical Abstract Generation for Academic Papers
Takuro Kawada, Shunsuke Kitada, Hitoshi Iyatomi
Graphical Abstracts (GAs) visually summarize the key findings of academic papers, playing a crucial role in facilitating the understanding of research content. Recently, advancemen…
TAUE: Training-free Noise Transplant and Cultivation Diffusion Model
Daichi Nagai, Ryugo Morita, Shunsuke Kitada +1
Despite the remarkable success of text-to-image diffusion models, their output of a single, flattened image remains a critical bottleneck for professional applications requiring la…
Robust Plant Disease Diagnosis with Few Target-Domain Samples
Takafumi Nogami, Satoshi Kagiwada, Hitoshi Iyatomi
Various deep learning-based systems have been proposed for accurate and convenient plant disease diagnosis, achieving impressive performance. However, recent studies show that thes…
SciGA: A Comprehensive Dataset for Designing Graphical Abstracts in Academic Papers
Takuro Kawada, Shunsuke Kitada, Sota Nemoto +1
Graphical Abstracts (GAs) play a crucial role in visually conveying the key findings of scientific papers. Although recent research increasingly incorporates visual materials such…
DDD: Discriminative Difficulty Distance for plant disease diagnosis
Yuji Arima, Satoshi Kagiwada, Hitoshi Iyatomi
Recent studies on plant disease diagnosis using machine learning (ML) have highlighted concerns about the overestimated diagnostic performance due to inappropriate data partitionin…
Few-shot Metric Domain Adaptation: Practical Learning Strategies for an Automated Plant Disease Diagnosis
Shoma Kudo, Satoshi Kagiwada, Hitoshi Iyatomi
Numerous studies have explored image-based automated systems for plant disease diagnosis, demonstrating impressive diagnostic capabilities. However, recent large-scale analyses hav…
Extended Japanese Commonsense Morality Dataset with Masked Token and Label Enhancement
Takumi Ohashi, Tsubasa Nakagawa, Hitoshi Iyatomi
Rapid advancements in artificial intelligence (AI) have made it crucial to integrate moral reasoning into AI systems. However, existing models and datasets often overlook regional…
Investigation to answer three key questions concerning plant pest identification and development of a practical identification framework
Ryosuke Wayama, Yuki Sasaki, Satoshi Kagiwada +2
The development of practical and robust automated diagnostic systems for identifying plant pests is crucial for efficient agricultural production. In this paper, we first investiga…
Hierarchical Object Detection and Recognition Framework for Practical Plant Disease Diagnosis
Kohei Iwano, Shogo Shibuya, Satoshi Kagiwada +1
Recently, object detection methods (OD; e.g., YOLO-based models) have been widely utilized in plant disease diagnosis. These methods demonstrate robustness to distance variations a…
Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition
Sota Nemoto, Shunsuke Kitada, Hitoshi Iyatomi
Data imbalance presents a significant challenge in various machine learning (ML) tasks, particularly named entity recognition (NER) within natural language processing (NLP). NER ex…
Practical X-ray Gastric Cancer Diagnostic Support Using Refined Stochastic Data Augmentation and Hard Boundary Box Training
Hideaki Okamoto, Quan Huu Cap, Takakiyo Nomura +3
Endoscopy is widely used to diagnose gastric cancer and has a high diagnostic performance, but it must be performed by a physician, which limits the number of people who can be dia…