Search Results for author:
Found 19 papers, 7 papers with code
CAT: Contrastive Adapter Training for Personalized Image Generation
Finally, we mention the possibility of CAT in the aspects of multi-concept adapter and optimization.
Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection
In this study, we introduce a novel component segmentation model for LA detection that leverages a few labeled samples and unlabeled images sharing logical constraints.
ABCD: Arbitrary Bitwise Coefficient for De-Quantization
Modern displays and contents support more than 8bits image and video.
Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model
As acquiring MRIs is expensive, neuroscience studies struggle to attain a sufficient number of them for properly training deep learning models.
Feature Re-calibration based Multiple Instance Learning for Whole Slide Image Classification
Whole slide image (WSI) classification is a fundamental task for the diagnosis and treatment of diseases; but, curation of accurate labels is time-consuming and limits the application of fully-supervised methods.
CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification
Few-shot classification is a challenging problem that aims to learn a model that can adapt to unseen classes given a few labeled samples.
Uncertainty-Aware Semi-Supervised Few Shot Segmentation
During inference, query segmentation is predicted using prototypes from both support and unlabeled images including low-level features of the query images.
Content Preserving Image Translation with Texture Co-occurrence and Spatial Self-Similarity for Texture Debiasing and Domain Adaptation
Models trained on datasets with texture bias usually perform poorly on out-of-distribution samples since biased representations are embedded into the model.
First Demonstration of the Korean eLoran Accuracy in a Narrow Waterway Using Improved ASF Maps
This letter briefly summarizes the efforts of South Korea to deploy an enhanced long-range navigation (eLoran) system, which is a terrestrial low-frequency radio navigation system that can complement GNSSs.
A Meta-Learning Approach for Medical Image Registration
To quickly adapt to various tasks, the meta learner was updated to get close to the center of parameters which are fine-tuned for each registration task.
Self-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs
The proposed ensemble noise model can generate realistic CT noise, and thus our method significantly improves the denoising performance existing denoising models trained by supervised- and self-supervised learning.
Mixing-AdaSIN: Constructing a De-biased Dataset using Adaptive Structural Instance Normalization and Texture Mixing
Our experiments show that classifiers trained with de-biased generated images report improved in-distribution performance and generalization on an external COVID-19 dataset.
Graphene plasmon-phonon coupled modes at the exceptional point
Properties of graphene plasmons are greatly affected by their coupling to phonons.
Mesoscale and Nanoscale Physics
Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation
In this paper, we propose a 3D few shot segmentation framework for accurate organ segmentation using limited training samples of the target organ annotation.
Multiple Instance Learning with Center Embeddings for Histopathology Classification
To address this, recent methods have considered WSI classification as a Multiple Instance Learning (MIL) problem often with a multi-stage process for learning instance and slide level features.
Few-Shot Relation Learning with Attention for EEG-based Motor Imagery Classification
In addition to the unified learning of feature similarity and a few shot classifier, our method leads to emphasize informative features in support data relevant to the query data, which generalizes better on unseen subjects.
2018 Robotic Scene Segmentation Challenge
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models.
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Segmentation methods had to be containerized and submitted to the challenge organizers.
Facial expression recognition based on local region specific features and support vector machines
But, in this paper we extracted region specific appearance features by dividing the whole face region into domain specific local regions.
