1 citations · 3 across the 11 of their papers we have counts for
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Test-time Adaptation for Regression by Subspace Alignment
Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai +1
This paper investigates test-time adaptation (TTA) for regression, where a regression model pre-trained in a source domain is adapted to an unknown target distribution with unlabel…
Evaluating Time-Series Training Dataset through Lens of Spectrum in Deep State Space Models
Sekitoshi Kanai, Yasutoshi Ida, Kazuki Adachi +3
This study investigates a method to evaluate time-series datasets in terms of the performance of deep neural networks (DNNs) with state space models (deep SSMs) trained on the data…
Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching
Shohei Enomoto, Naoya Hasegawa, Kazuki Adachi +4
Deep neural networks have achieved remarkable success in a variety of computer vision applications. However, there is a problem of degrading accuracy when the data distribution shi…
Test-time Similarity Modification for Person Re-identification toward Temporal Distribution Shift
Kazuki Adachi, Shohei Enomoto, Taku Sasaki +1
Person re-identification (re-id), which aims to retrieve images of the same person in a given image from a database, is one of the most practical image recognition applications. In…
Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks
Shin'ya Yamaguchi, Sekitoshi Kanai, Kazuki Adachi +1
While fine-tuning is a de facto standard method for training deep neural networks, it still suffers from overfitting when using small target datasets. Previous methods improve fine…