203 Result(s)
within
English
Artificial Intelligence
Computer Imaging, Vision, Pattern Recognition and Graphics
**-**a Ding
Chapter
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Chapter and Conference Paper
IoT Botnet Attacks Detection and Classification Based on Ensemble Learning
With the vigorous development of the IoT, botnet attacks against the IoT have become more frequent and diverse, and the research on attack prevention and detection has become more difficult. This paper propose...
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Chapter and Conference Paper
Infrared and Visible Image Fusion via Test-Time Training
Infrared and visible image fusion (IVIF) is a widely used technique in instrument-related fields. It aims at extracting contrast information from the infrared image and texture details from the visible image a...
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Chapter and Conference Paper
Prediction and Analysis of Multiple Causes of Mental Health Problems Based on Machine Learning
To prevent other types of mental health problems from being misclassified as depression, as well as to remedy the problem of inadequate resources for mental health consultations. This study first analyzes the ...
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Chapter and Conference Paper
DP-INNet: Dual-Path Implicit Neural Network for Spatial and Spectral Features Fusion in Pan-Sharpening
Pan-sharpening is a technique that fuses a high-resolution panchromatic (PAN) image with its corresponding low-resolution multispectral (MS) image to create a high-resolution multispectral image. Due to the po...
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Chapter and Conference Paper
Fast QTMT Decision for H.266/VVC via Jointly Leveraging Neural Network and Machine Learning Models
The latest video coding standard H.266/VVC has significantly improved the compression efficiency compared to its predecessor H.265/HEVC. One of the key technologies in H.266/VVC is the QuadTree with nested Mul...
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Chapter and Conference Paper
Graph-Based Dependency-Aware Non-Intrusive Load Monitoring
Non-intrusive load monitoring (NILM) is able to analyze and predict users’ power consumption behaviors for further improving the power consumption efficiency of the grid. Neural network-based techniques have b...
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Chapter and Conference Paper
Learning Scene Graph for Better Cross-Domain Image Captioning
The current image captioning (IC) methods achieve good results within a single domain primarily due to training on a large amount of annotated data. However, the performance of single-domain image captioning m...
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Chapter and Conference Paper
Design of Distributed Synchronization Header for Short Burst Communication with Low Earth Orbit Satellites
With the rapid development of low Earth orbit satellite communication technology, achieving efficient communication in multi-user access scenarios has become a highly regarded challenge. The associated frame s...
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Chapter and Conference Paper
MTMG: A Framework for Generating Adversarial Examples Targeting Multiple Learning-Based Malware Detection Systems
As machine learning technology continues to advance rapidly, an increasing number of researchers are utilizing it in the field of malware detection. Despite the fact that learning-based malware detection syste...
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Chapter and Conference Paper
Recognizer Embedding Diffusion Generation for Few-Shot SAR Recognization
Synthetic Aperture Radar (SAR) has become a research hotspot due to its ability to identify targets in all weather conditions and at all times. To achieve satisfactory recognition performance in most existing ...
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Chapter and Conference Paper
A Two-Stage Federated Learning Framework for Class Imbalance in Aerial Scene Classification
Centralized aerial imagery analysis techniques face two challenges. The first one is the data silos problem, where data is located at different organizations separately. The second challenge is the class imbal...
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Chapter and Conference Paper
Fuzzy Sliding Mode Trajectory Tracking Control for Omnidirectional Mobile Robots Based on Exponential Convergence Law
The increasing advancements in information technology have led to a growing interest in control research for mobile robot trajectory tracking. A controller for robot systems should exhibit adaptivity and robus...
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Chapter and Conference Paper
Boosting Generalization Performance in Person Re-identification
Generalizable person re-identification (ReID) has gained significant attention in recent years as it poses greater challenges in recognizing individuals across different domains and unseen scenarios. Existing ...
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Chapter and Conference Paper
Unsupervised Contrastive Learning of Sentence Embeddings Through Optimized Sample Construction and Knowledge Distillation
Unsupervised contrastive learning of sentence embedding has been a recent focus of researchers. However, issues such as unreasonable division of positive and negative samples and poor data enhancement leading ...
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Chapter and Conference Paper
Sem-Avatar: Semantic Controlled Neural Field for High-Fidelity Audio Driven Avatar
In this paper, we tackle the audio-driven avatar challenge by fitting a semantic controlled neural field to a talking-head video. While existing methods struggle with realism and head-torso inconsistency, our ...
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Chapter and Conference Paper
Lightweight Multispectral Skeleton and Multi-stream Graph Attention Networks for Enhanced Action Prediction with Multiple Modalities
Human action recognition methods often focus on extracting structural and temporal information from skeleton-based graphs. However, these approaches struggle with effectively capturing and processing extensive...
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Chapter and Conference Paper
Unsupervised Domain Adaptation for Optical Flow Estimation
In recent years, we have witnessed significant breakthroughs of optical flow estimation with the thriving of deep learning. The performance of the unsupervised method is unsatisfactory due to it is lack of eff...
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Chapter and Conference Paper
Self-agreement: A Framework for Fine-Tuning Language Models to Find Agreement Among Diverse Opinions
Finding an agreement among diverse opinions is a challenging topic in social intelligence. Recently, large language models (LLMs) have shown great potential in addressing this challenge due to their remarkable...
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Chapter and Conference Paper
A Deep Reinforcement Learning Based Facilitation Agent for Consensus Building Among Multi-Round Discussions
Achieving consensus among diverse opinions through multi-round discussions can be a complex process. The advent of large language models (LLMs) offers promising avenues for resolving this challenge, given thei...
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Chapter and Conference Paper
MARL \(_{4}DRP\) : Benchmarking Cooperative Multi-agent Reinforcement Learning Algorithms for Drone Routing Problems
The use of drones as an efficient delivery solution is a promising technology, addressing the growing demand for deliveries. Unlike the traditional vehicle routing problem (VRP), we introduce a new drone routi...
