62 citations · 80 across the 16 of their papers we have counts for
6 papers · 1 filter
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…