Search Results for author:
Found 10 papers, 3 papers with code
DocTTT: Test-Time Training for Handwritten Document Recognition Using Meta-Auxiliary Learning
During testing, we adapt the visual representation parameters using a self-supervised MAE loss.
Tackling Small Sample Survival Analysis via Transfer Learning: A Study of Colorectal Cancer Prognosis
For non-parametric models such as Random Survival Forest, we propose a new transfer survival forest (TSF) model that transfers tree structures from source tasks and fine-tunes them with target data.
Distribution Alignment for Fully Test-Time Adaptation with Dynamic Online Data Streams
Given a model trained on source data, Test-Time Adaptation (TTA) enables adaptation and inference in test data streams with domain shifts from the source.
Ontology-aware Network for Zero-shot Sketch-based Image Retrieval
Zero-Shot Sketch-Based Image Retrieval (ZSSBIR) is an emerging task.
Fully Automated Deep Learning-enabled Detection for Hepatic Steatosis on Computed Tomography: A Multicenter International Validation Study
To automate the process, we validated an existing artificial intelligence (AI) system for 3D liver segmentation and used it to purpose a novel method: AI-ROI, which could automatically select the ROI for attenuation measurements.
A Computational Efficient Maximum Likelihood Direct Position Determination Approach for Multiple Emitters Using Angle and Doppler Measurements
Emitter localization is widely applied in the military and civilian _elds.
Spatio-Temporal Self-Attention Network for Video Saliency Prediction
3D convolutional neural networks have achieved promising results for video tasks in computer vision, including video saliency prediction that is explored in this paper.
Cascade of correlated electron states in a kagome superconductor CsV3Sb5
At a temperature far above the superconducting transition Tc ~ 2. 5 K, we reveal a tri-directional charge order with a 2a0 period that breaks the translation symmetry of the lattice.
Superconductivity Strongly Correlated Electrons
Nanoscale decoupling of electronic nematicity and structural anisotropy in FeSe thin films
In this work, we discover that electronic nematicity can be locally decoupled from the underlying structural anisotropy in strain-engineered iron-selenide (FeSe) thin films.
Strongly Correlated Electrons Materials Science Superconductivity
Discovery of unconventional chiral charge order in kagome superconductor KV3Sb5
Here we use high-resolution scanning tunnelling microscopy (STM) to discover an unconventional charge order in a kagome material KV3Sb5, with both a topological band structure and a superconducting ground state.
Superconductivity Materials Science Strongly Correlated Electrons
