2,521 Result(s)
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Chapter and Conference Paper
Swin-MMC: Swin-Based Model for Myopic Maculopathy Classification in Fundus Images
Myopic maculopathy is a highly myopic retinal disorder that often occurs in highly myopic patients, serving as a major cause of visual impairment and blindness in numerous countries. Currently, fundus images s...
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Chapter and Conference Paper
Boosting One-Stage Multi Object Tracking with Attention Learning
One-stage multi-object tracking methods have achieved promising results by showing their great balance between accuracy and speed. However, the internal differences and relationships between detection and re-i...
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Chapter and Conference Paper
Cross-Modal Transformer GAN: A Brain Structure-Function Deep Fusing Framework for Alzheimer’s Disease
Cross-modal fusion of different types of neuroimaging data has shown great promise for predicting the progression of Alzheimer’s Disease(AD). However, most existing methods applied in neuroimaging can not effi...
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Chapter and Conference Paper
Research on Wavelet Packet Sample Entropy Features of sEMG Signal in Lower Limb Movement Recognition
In order to extract deeper features from surface electromyography signals and improve the classification accuracy of lower limb movements, a feature extraction method combining wavelet packet and sample entrop...
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Chapter and Conference Paper
CFNet: A Coarse-to-Fine Framework for Coronary Artery Segmentation
Coronary Artery (CA) segmentation has become an important task to facilitate coronary artery disease diagnosis. However, existing methods have not effectively addressed the challenges posed by the thin and com...
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Chapter and Conference Paper
Fault Diagnosis with BERT Bi-LSTM-assisted Knowledge Graph Aided by Attention Mechanism for Hydro-Power Plants
To minimize the risk of Hydro-Power Plant failure, it’s crucial to detect and precisely repair the damaged components. In this paper, we propose a knowledge graph-based fault diagnosis method for Hydro-Power P...
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Chapter and Conference Paper
Research on Tongue Muscle Strength Measurement and Recovery System
Dysphagia is caused by movement disorders such as muscular systems or neurological diseases that participate in speech movement. Speech difficulty sufferers as the main victim of Dysphagia often have problems ...
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Chapter and Conference Paper
Customized Anchors Can Better Fit the Target in Siamese Tracking
Most existing siamese trackers rely on some fixed anchors to estimate the scale and aspect ratio for all targets. However, in real tracking, different targets have different sizes and shapes, these predefined ...
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Chapter and Conference Paper
A Domain Adaptation Deep Learning Network for EEG-Based Motor Imagery Classification
The correlation between neighboring electroencephalography (EEG) channels reveals brain signal interconnectedness, and how to represent this correlation is being studied. Simultaneously, variations in EEG sign...
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Chapter and Conference Paper
SC-Chain: A Multi-modal Collaborative Storage System for Medical Resources
At present, collaborative healthcare faces a series of problems such as inconsistent standards, prominent information silos, and inadequate information security management. Because of this, the application of ...
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Chapter and Conference Paper
The New Paradigm of Safe and Sustainable Transportation: Urban Air Mobility
Urban Air Mobility (UAM) is a revolutionary air transportation system that enables on-demand air travel. To enable successful air transportation, efficient management of large-scale aircraft is a critical fact...
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Chapter and Conference Paper
Label Selection Algorithm Based on Ant Colony Optimization and Reinforcement Learning for Multi-label Classification
Multi-label classification handles scenarios where an instance can be annotated with multiple non-exclusive but semantically related labels simultaneously. Despite significant progress, multi-label classificat...
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Chapter and Conference Paper
Road Meteorological State Recognition in Extreme Weather Based on an Improved Mask-RCNN
Road surface condition (RSC) is an important indicator for road maintenance departments to survey, inspect, clean, and repair roads. The number of traffic accidents can increase dramatically in winter or durin...
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Chapter and Conference Paper
ε-Maximum Critic Deep Deterministic Policy Gradient for Multi-agent Reinforcement Learning
In Multi-Agent Reinforcement Learning, the agents are vulnerable to the other agents and the training environment, which can lead to agents’ policy achieving a local optima easily and poor convergence efficien...
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Chapter and Conference Paper
Exploration and Application Based on Authentication, Authorization, Accounting in Home Broadband Scenario
With the rapid development of broadband market services, Internet Service Providers (ISPs) strive to improve the end-to-end network quality of home broadband. However, faced with the opaque and unknown indoor ...
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Chapter and Conference Paper
Matching-to-Detecting: Establishing Dense and Reliable Correspondences Between Images
We present a novel view for local image feature matching, which is inspired by the difference between existing methods. Detector-based methods detect predefined keypoints in local regions, so that the stabilit...
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Chapter and Conference Paper
L2T-BEV: Local Lane Topology Prediction from Onboard Surround-View Cameras in Bird’s Eye View Perspective
High definition maps (HDMaps) serve as the foundation for autonomous vehicles, encompassing various driving scenario elements, among which lane topology is critically important for vehicle perception and plann...
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Chapter and Conference Paper
Flood Adventures: Evaluation Study of Final Prototype
It is vital that individuals of all ages know what preparations to make prior to a flooding event and what actions to take during an actual flood event. To address this, we have designed and developed a fully ...
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Chapter and Conference Paper
Segment Anything Model for Semi-supervised Medical Image Segmentation via Selecting Reliable Pseudo-labels
Semi-supervised learning (SSL) has become a hot topic due to its less dependence on annotated data compared to fully supervised methods. This advantage becomes more evident in the field of medical imaging, whe...
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Chapter and Conference Paper
A Framework Combining Separate and Joint Training for Neural Vocoder-Based Monaural Speech Enhancement
Conventional single-channel speech enhancement methodologies have predominantly emphasized the enhancement of the amplitude spectrum while preserving the original phase spectrum. Nonetheless, this may introduc...
