Search Results for author:
Found 27 papers, 1 papers with code
Enhanced Sparse Model for Blind Deblurring
Specifically, we use a weighted combination of a dense function (i. e. l2) and a newly designed enhanced sparse model termed as le, which is developed from two sparse models (i. e. l1 and l0), to fulfill the task.
Learning pseudo-contractive denoisers for inverse problems
A training strategy based on holomorphic transformation and functional calculi is proposed to enforce the pseudo-contractive denoiser assumption.
MIFI: MultI-camera Feature Integration for Roust 3D Distracted Driver Activity Recognition
Distracted driver activity recognition plays a critical role in risk aversion-particularly beneficial in intelligent transportation systems.
Learning Implicit Representation for Reconstructing Articulated Objects
Our method simultaneously estimates the visible (explicit) representation (3D shapes, colors, camera parameters) and the implicit skeletal representation, from motion cues in the object video without 3D supervision.
CSL: Class-Agnostic Structure-Constrained Learning for Segmentation Including the Unseen
Addressing Out-Of-Distribution (OOD) Segmentation and Zero-Shot Semantic Segmentation (ZS3) is challenging, necessitating segmenting unseen classes.
Open-NeRF: Towards Open Vocabulary NeRF Decomposition
Current techniques for NeRF decomposition involve a trade-off between the flexibility of processing open-vocabulary queries and the accuracy of 3D segmentation.
Explainable Graph Neural Network for Alzheimer's Disease And Related Dementias Risk Prediction
Employing a GNN approach with claims data enhances ADRD risk prediction and provides insights into the impact of interconnected medical code relationships.
Distributionally Robust Cross Subject EEG Decoding
In this work, we propose a principled approach to perform dynamic evolution on the data for improvement of decoding robustness.
OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and Dialogue
We introduce visual ability into the large language model to complete the ophthalmic large language and vision assistant (OphGLM).
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
Graph representation learning (GRL) has emerged as a pivotal field that has contributed significantly to breakthroughs in various fields, including biomedicine.
Learning Person-specific Network Representation for Apparent Personality Traits Recognition
In this paper, we propose to recognize apparent personality recognition approach which first trains a person-specific network for each subject, modelling multi-scale long-term person-specific behavior evolution of the subject.
Multi-Sem Fusion: Multimodal Semantic Fusion for 3D Object Detection
Most multi-modal 3D object detection frameworks integrate semantic knowledge from 2D images into 3D LiDAR point clouds to enhance detection accuracy.
Domain-specific Learning of Multi-scale Facial Dynamics for Apparent Personality Traits Prediction
Human personality decides various aspects of their daily life and working behaviors.
Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference
Deep learning techniques have shown great potential in medical image processing, particularly through accurate and reliable image segmentation on magnetic resonance imaging (MRI) scans or computed tomography (CT) scans, which allow the localization and diagnosis of lesions.
Mining On Alzheimer's Diseases Related Knowledge Graph to Identity Potential AD-related Semantic Triples for Drug Repurposing
The 1, 672, 110 filtered triples were used to train with knowledge graph completion algorithms (i. e., TransE, DistMult, and ComplEx) to predict candidates that might be helpful for AD treatment or prevention.
Training Generative Adversarial Networks with Adaptive Composite Gradient
Nevertheless, designing an efficient and competitive training method is still a challenging task due to the cyclic behaviors of some gradient-based ways and the expensive computational cost of these methods based on the Hessian matrix.
CASPR: A Commonsense Reasoning-based Conversational Socialbot
We present the philosophy behind CASPR's design as well as details of its implementation.
DiscASP: A Graph-based ASP System for Finding Relevant Consistent Concepts with Applications to Conversational Socialbots
We consider the problem of finding relevant consistent concepts in a conversational AI system, particularly, for realizing a conversational socialbot.
Knowledge Graph-based Neurodegenerative Diseases and Diet Relationship Discovery
To date, there are no effective treatments for most neurodegenerative diseases.
Knowledge-Assisted Reasoning of Model-Augmented System Requirements with Event Calculus and Goal-Directed Answer Set Programming
We also show how answer set programming (ASP) and its query-driven implementation s(CASP) can be used to directly realize the event calculus model of the requirements.
grASP: A Graph Based ASP-Solver and Justification System
As a result, justification for why a literal is in the answer set is hard to produce.
A Novel Retinex-Based Fractional-Order Variational Model for Image with Severely Low Light
The proposed method is more flexible in controlling the reg- ularization extent than the existing integer-order regularization methods.
Zero-Shot Recognition through Image-Guided Semantic Classification
Motivated by the binary relevance method for multi-label classification, we propose to inversely learn the mapping between an image and a semantic classifier.
Encoding Sentiment Information into Word Vectors for Sentiment Analysis
General-purpose pre-trained word embeddings have become a mainstay of natural language processing, and more recently, methods have been proposed to encode external knowledge into word embeddings to benefit specific downstream tasks.
Group Linguistic Bias Aware Neural Response Generation
For practical chatbots, one of the essential factor for improving user experience is the capability of customizing the talking style of the agents, that is, to make chatbots provide responses meeting users{'} preference on language styles, topics, etc.
Generative Adversarial Network based on Resnet for Conditional Image Restoration
The GANs promote an adversarive game to approximate complex and jointed example probability.
A Multiphase Image Segmentation Based on Fuzzy Membership Functions and L1-norm Fidelity
In this paper, we propose a variational multiphase image segmentation model based on fuzzy membership functions and L1-norm fidelity.
