5 citations · 6 across the 7 of their papers we have counts for
7 papers
Feature Space Analysis by Guided Diffusion Model
Kimiaki Shirahama, Miki Yanobu, Kaduki Yamashita +1
This paper aims to analyse the feature space of a vision-related Deep Neural Network (DNN) by proposing a decoder that can generate an image whose feature closely matches a user-sp…
Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence Generation
Zihao Chen, Hisashi Handa, Miho Ohsaki +1
Several backbone models pre-trained on general domain datasets can encode a sentence into a widely useful embedding. Such sentence embeddings can be further enhanced by domain adap…
JCSE: Contrastive Learning of Japanese Sentence Embeddings and Its Applications
Zihao Chen, Hisashi Handa, Kimiaki Shirahama
Contrastive learning is widely used for sentence representation learning. Despite this prevalence, most studies have focused exclusively on English and few concern domain adaptatio…
Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features
Frank Kulwa, Chen Li, Marcin Grzegorzek +3
The use of Environmental Microorganisms (EMs) offers a highly efficient, low cost and harmless remedy to environmental pollution, by monitoring and decomposing of pollutants. This…
Embedding-based Music Emotion Recognition Using Composite Loss
Naoki Takashima, Frédéric Li, Marcin Grzegorzek +1
Most music emotion recognition approaches perform classification or regression that estimates a general emotional category from a distribution of music samples, but without conside…
Generic Itemset Mining Based on Reinforcement Learning
Kazuma Fujioka, Kimiaki Shirahama
One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets. To ov…
A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysis
Frank Kulwa, Chen Li, Jinghua Zhang +6
Environmental microorganism (EM) offers a high-efficient, harmless, and low-cost solution to environmental pollution. They are used in sanitation, monitoring, and decomposition of…