1 citations · 3 across the 4 of their papers we have counts for
6 papers
Inter-Feature-Map Differential Coding of Surveillance Video
Kei Iino, Miho Takahashi, Hiroshi Watanabe +5
In Collaborative Intelligence, a deep neural network (DNN) is partitioned and deployed at the edge and the cloud for bandwidth saving and system optimization. When a model input is…
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…
Improving Image Coding for Machines through Optimizing Encoder via Auxiliary Loss
Kei Iino, Shunsuke Akamatsu, Hiroshi Watanabe +3
Image coding for machines (ICM) aims to compress images for machine analysis using recognition models rather than human vision. Hence, in ICM, it is important for the encoder to re…
Incorporating Supervised Domain Generalization into Data Augmentation
Shohei Enomoto, Monikka Roslianna Busto, Takeharu Eda
With the increasing utilization of deep learning in outdoor settings, its robustness needs to be enhanced to preserve accuracy in the face of distribution shifts, such as compressi…
Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems
Shohei Enomoto, Takeharu Eda
Recently, deep neural networks have become to be used in a variety of applications. While the accuracy of deep neural networks is increasing, the confidence score, which indicates…