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Found 19 papers, 1 papers with code
Deep Representation Learning for Multi-functional Degradation Modeling of Community-dwelling Aging Population
As the aging population grows, particularly for the baby boomer generation, the United States is witnessing a significant increase in the elderly population experiencing multifunctional disabilities.
Neurological disorders leading to mechanical dysfunction of the esophagus: an emergent behavior of a neuromechanical dynamical system
Specifically, repetitive antegrade contractions (RACs) are conclusively shown to emerge from the coupled neuromechanical dynamics in response to sustained volumetric distension.
MEDs for PETs: Multilingual Euphemism Disambiguation for Potentially Euphemistic Terms
This study investigates the computational processing of euphemisms, a universal linguistic phenomenon, across multiple languages.
Text Classification Based on Knowledge Graphs and Improved Attention Mechanism
To resolve the semantic ambiguity in texts, we propose a model, which innovatively combines a knowledge graph with an improved attention mechanism.
Guided Image Restoration via Simultaneous Feature and Image Guided Fusion
Currently, joint image filtering-inspired deep learning-based methods represent the state-of-the-art for GIR tasks.
Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration
GOLD distills an offline DT policy into a lightweight policy network through guided online safe RL training, which outperforms both the offline DT policy and online safe RL algorithms.
Completing point cloud from few points by Wasserstein GAN and Transformers
Inspired by the successful applications of GAN and Transformers in the image-based vision task, we introduce GAN and Transformer techniques to address the above problem.
Tensor Recovery Based on A Novel Non-convex Function Minimax Logarithmic Concave Penalty Function
The proposed function is generalized to tensor cases, yielding tensor MLCP and weighted tensor $L\gamma$-norm.
LiDAR-guided Stereo Matching with a Spatial Consistency Constraint
Next, we propose a riverbed enhancement function to optimize the cost volume of the LiDAR projection points and their homogeneous pixels to improve the matching robustness.
Low-light Image Enhancement by Retinex Based Algorithm Unrolling and Adjustment
Besides, to avoid manually parameter tuning, we also propose a self-supervised fine-tuning strategy, which can always guarantee a promising performance.
Low-Rank Tensor Completion Based on Bivariate Equivalent Minimax-Concave Penalty
To makes all the constant parameters of the MCP function as variables so that futherly improving the adaptability to the change of singular values in the LRTC problem, we propose the bivariate equivalent minimax-concave penalty (BEMCP) theorem.
ELSR: Efficient Line Segment Reconstruction With Planes and Points Guidance
In this paper, we propose an efficient line segment reconstruction method called ELSR.
Emergency Vehicles Audio Detection and Localization in Autonomous Driving
Hence, all other vehicles are supposed to take proper actions to yield emergency vehicles with active sirens.
Tensor Full Feature Measure and Its Nonconvex Relaxation Applications to Tensor Recovery
Tensor sparse modeling as a promising approach, in the whole of science and engineering has been a huge success.
Two New Low Rank Tensor Completion Methods Based on Sum Nuclear Norm
This paper proposes a new tensor $L_{2, 1}$ norm minimization model (TLNM) that integrates sum nuclear norm (SNN) method, differing from the classical tensor nuclear norm (TNN)-based tensor completion method, with $L_{2, 1}$ norm and Qatar Riyal decomposition for solving the LRTC problem.
Cancer image classification based on DenseNet model
Computer-aided diagnosis establishes methods for robust assessment of medical image-based examination.
Transfer Learning Robustness in Multi-Class Categorization by Fine-Tuning Pre-Trained Contextualized Language Models
This study compares the effectiveness and robustness of multi-class categorization of Amazon product data using transfer learning on pre-trained contextualized language models.
Behavior Pattern and Compiled Information Based Performance Prediction in MOOCs
This paper mainly focuses on the students' accomplishment behaviors in programming assignments and compiled information from programming assignments.
A Collaborative Approach to Angel and Venture Capital Investment Recommendations
With a similar model, the same dataset was used to generate investor recommendations for companies undergoing fundraising, which achieved highest prediction accuracy of 11. 1%.
