Search Results for author:
Found 11 papers, 5 papers with code
Incremental Pseudo-Labeling for Black-Box Unsupervised Domain Adaptation
Black-Box unsupervised domain adaptation (BBUDA) learns knowledge only with the prediction of target data from the source model without access to the source data and source model, which attempts to alleviate concerns about the privacy and security of data.
Frequency-Guided Multi-Level Human Action Anomaly Detection with Normalizing Flows
We introduce the task of human action anomaly detection (HAAD), which aims to identify anomalous motions in an unsupervised manner given only the pre-determined normal category of training action samples.
An Efficient Reconstructed Differential Evolution Variant by Some of the Current State-of-the-art Strategies for Solving Single Objective Bound Constrained Problems
In this paper, we propose a strategy recombination and reconstruction differential evolution algorithm called reconstructed differential evolution (RDE) to solve single-objective bounded optimization problems.
Complex-Valued Convolutional Gated Recurrent Neural Network for Ultrasound Beamforming
The complex-valued network operations proposed in this study improve the beamforming accuracy of complex-valued ultrasound signals over traditional real-valued methods.
Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction
In our experiments, MSU extracts one point from a velocity field containing 121 points and utilizes this point to accurately predict 100 pressure points on the cylinder.
Dendritic Learning-incorporated Vision Transformer for Image Recognition
DVT is a groundbreaking Biomimetic Vision Transformer that combines dendritic learning and Vision Transformer architecture, showcasing superior image recognition performance through biologically inspired structures.
A Multi-In and Multi-Out Dendritic Neuron Model and its Optimization
Recently, a novel mathematical ANN model, known as the dendritic neuron model (DNM), has been proposed to address nonlinear problems by more accurately reflecting the structure of real neurons.
Pareto Dominance Archive and Coordinated Selection Strategy-Based Many-Objective Optimizer for Protein Structure Prediction
One of the efficient tools to describe this information is protein energy functions.
Differentiable Search of Accurate and Robust Architectures
Deep neural networks (DNNs) are found to be vulnerable to adversarial attacks, and various methods have been proposed for the defense.
A Cascade Dual-Decoder Model for Joint Entity and Relation Extraction
In this work, we propose an effective cascade dual-decoder method to extract overlapping relational triples, which includes a text-specific relation decoder and a relation-corresponded entity decoder.
ASBSO: An Improved Brain Storm Optimization With Flexible Search Length and Memory-Based Selection
This proposed method, adaptive step length based on memory selection BSO, namely ASBSO, applies multiple step lengths to modify the generation process of new solutions, thus supplying a flexible search according to corresponding problems and convergent periods.
