Search Results for author:
Found 14 papers, 6 papers with code
Fair Contrastive Learning for Facial Attribute Classification
Through extensive experiments on CelebA and UTK Face, we validate that the proposed method significantly outperforms SupCon and existing state-of-the-art methods in terms of the trade-off between top-1 accuracy and fairness.
Distance-aware Quantization
This alleviates the gradient mismatch, but causes a quantizer gap problem.
Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy
A shift-invariant variational autoencoder (shift-VAE) is developed as an unsupervised method for the analysis of spectral data in the presence of shifts along the parameter axis, disentangling the physically-relevant shifts from other latent variables.
Network Quantization with Element-wise Gradient Scaling
Network quantization aims at reducing bit-widths of weights and/or activations, particularly important for implementing deep neural networks with limited hardware resources.
VOTE400(Voide Of The Elderly 400 Hours): A Speech Dataset to Study Voice Interface for Elderly-Care
This paper introduces a large-scale Korean speech dataset, called VOTE400, that can be used for analyzing and recognizing voices of the elderly people.
FairFaceGAN: Fairness-aware Facial Image-to-Image Translation
Further, we also evaluate image translation performances, where FairFaceGAN shows competitive results, compared to those of existing methods.
Learning with Privileged Information for Efficient Image Super-Resolution
The student and the decoder in the teacher, having the same network architecture as FSRCNN, try to reconstruct HR images.
README: REpresentation learning by fairness-Aware Disentangling MEthod
After the representation learning, this disentangled representation is leveraged for fairer downstream classification by excluding the subspace with the protected attribute information.
ETRI-Activity3D: A Large-Scale RGB-D Dataset for Robots to Recognize Daily Activities of the Elderly
To cope with this situation, we introduce a new dataset called ETRI-Activity3D, focusing on the daily activities of the elderly in robot-view.
Super-resolution and signal separation in contact Kelvin Probe Force Microscopy of Electrochemically Active Ferroelectric Materials
Imaging mechanisms in contact Kelvin Probe Force Microscopy (cKPFM) are explored via information theory-based methods.
Applied Physics Materials Science
Learning Semantic Correspondence Exploiting an Object-level Prior
We address the problem of semantic correspondence, that is, establishing a dense flow field between images depicting different instances of the same object or scene category.
Imaging Mechanism for Hyperspectral Scanning Probe Microscopy via Gaussian Process Modelling
We investigate the ability to reconstruct and derive spatial structure from sparsely sampled 3D piezoresponse force microcopy data, captured using the band-excitation (BE) technique, via Gaussian Process (GP) methods.
Computational Physics Materials Science
SFNet: Learning Object-aware Semantic Correspondence
We address the problem of semantic correspondence, that is, establishing a dense flow field between images depicting different instances of the same object or scene category.
Squeezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things
In this paper, we propose Squeezed Convolutional Variational AutoEncoder (SCVAE) for anomaly detection in time series data for Edge Computing in Industrial Internet of Things (IIoT).
