62 citations · 97 across the 17 of their papers we have counts for
17 papers
Screening Is Effective for Visual Recognition
Shunya Shimomura, Kazuhiro Hotta
Vision Transformer (ViT) has been widely used as a powerful framework for modeling global dependencies among image patches. However, its core component, self-attention assigns soft…
Lite-HRNet Plus: Fast and Accurate Facial Landmark Detection
Sota Kato, Kazuhiro Hotta, Yuhki Hatakeyama +1
Facial landmark detection is an essential technology for driver status tracking and has been in demand for real-time estimations. As a landmark coordinate prediction, heatmap-based…
Enlarged Large Margin Loss for Imbalanced Classification
Sota Kato, Kazuhiro Hotta
We propose a novel loss function for imbalanced classification. LDAM loss, which minimizes a margin-based generalization bound, is widely utilized for class-imbalanced image classi…
DeformableFormer: Classification of Endoscopic Ultrasound Guided Fine Needle Biopsy in Pancreatic Diseases
Taiji Kurami, Takuya Ishikawa, Kazuhiro Hotta
Endoscopic Ultrasound-Fine Needle Aspiration (EUS-FNA) is used to examine pancreatic cancer. EUS-FNA is an examination using EUS to insert a thin needle into the tumor and collect…
One-shot and Partially-Supervised Cell Image Segmentation Using Small Visual Prompt
Sota Kato, Kazuhiro Hotta
Semantic segmentation of microscopic cell images using deep learning is an important technique, however, it requires a large number of images and ground truth labels for training.…
Reconstructed Student-Teacher and Discriminative Networks for Anomaly Detection
Shinji Yamada, Satoshi Kamiya, Kazuhiro Hotta
Anomaly detection is an important problem in computer vision; however, the scarcity of anomalous samples makes this task difficult. Thus, recent anomaly detection methods have used…
Adaptive t-vMF Dice Loss for Multi-class Medical Image Segmentation
Sota Kato, Kazuhiro Hotta
Dice loss is widely used for medical image segmentation, and many improvement loss functions based on such loss have been proposed. However, further Dice loss improvements are stil…
Adversarial Mutual Leakage Network for Cell Image Segmentation
Hiroki Tsuda, Kazuhiro Hotta
We propose three segmentation methods using GAN and information leakage between generator and discriminator. First, we propose an Adversarial Training Attention Module (ATA-Module)…
Localized Feature Aggregation Module for Semantic Segmentation
Ryouichi Furukawa, Kazuhiro Hotta
We propose a new information aggregation method which called Localized Feature Aggregation Module based on the similarity between the feature maps of an encoder and a decoder. The…
Reconstruction Student with Attention for Student-Teacher Pyramid Matching
Shinji Yamada, Kazuhiro Hotta
Anomaly detection and localization are important problems in computer vision. Recently, Convolutional Neural Network (CNN) has been used for visual inspection. In particular, the s…
Automatic Preprocessing and Ensemble Learning for Low Quality Cell Image Segmentation
Sota Kato, Kazuhiro Hotta
We propose an automatic preprocessing and ensemble learning for segmentation of cell images with low quality. It is difficult to capture cells with strong light. Therefore, the mic…
MSE Loss with Outlying Label for Imbalanced Classification
Sota Kato, Kazuhiro Hotta
In this paper, we propose mean squared error (MSE) loss with outlying label for class imbalanced classification. Cross entropy (CE) loss, which is widely used for image recognition…
Cell image segmentation by Feature Random Enhancement Module
Takamasa Ando, Kazuhiro Hotta
It is important to extract good features using an encoder to realize semantic segmentation with high accuracy. Although loss function is optimized in training deep neural network,…
Feature Sharing Cooperative Network for Semantic Segmentation
Ryota Ikedo, Kazuhiro Hotta
In recent years, deep neural networks have achieved high ac-curacy in the field of image recognition. By inspired from human learning method, we propose a semantic segmentation met…
Feedback Attention for Cell Image Segmentation
Hiroki Tsuda, Eisuke Shibuya, Kazuhiro Hotta
In this paper, we address cell image segmentation task by Feedback Attention mechanism like feedback processing. Unlike conventional neural network models of feedforward processing…
Feedback U-net for Cell Image Segmentation
Eisuke Shibuya, Kazuhiro Hotta
Human brain is a layered structure, and performs not only a feedforward process from a lower layer to an upper layer but also a feedback process from an upper layer to a lower laye…
Mixture of Counting CNNs: Adaptive Integration of CNNs Specialized to Specific Appearance for Crowd Counting
Shohei Kumagai, Kazuhiro Hotta, Takio Kurita
This paper proposes a crowd counting method. Crowd counting is difficult because of large appearance changes of a target which caused by density and scale changes. Conventional cro…