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Found 11 papers, 1 papers with code
WaveletFormerNet: A Transformer-based Wavelet Network for Real-world Non-homogeneous and Dense Fog Removal
However, the haze distribution in the real world is complex, and downsampling can lead to color distortion or loss of detail in the output results as the resolution of a feature map or image resolution decreases.
DedustNet: A Frequency-dominated Swin Transformer-based Wavelet Network for Agricultural Dust Removal
Compared to existing state-of-the-art methods, DedustNet achieves superior performance and more reliable results in agricultural image dedusting, providing strong support for the application of agricultural machinery in dusty environments.
Network-Wide Task Offloading With LEO Satellites: A Computation and Transmission Fusion Approach
To address the network-wide offloading problem, we propose a metagraph-based computation and transmission fusion offloading scheme for multi-tier networks.
Adaptive Task Offloading for Space Missions: A State-Graph-Based Approach
However, the overall delay is determined by both computation and transmission costs.
Quality-aware Part Models for Occluded Person Re-identification
Existing approaches typically rely on outside tools to infer visible body parts, which may be suboptimal in terms of both computational efficiency and ReID accuracy.
Blockchain-Based Decentralized Energy Management Platform for Residential Distributed Energy Resources in A Virtual Power Plant
In this paper, we develop a blockchain-based VPP energy management platform to facilitate a rich set of transactive energy activities among residential users with renewables, energy storage, and flexible loads in a VPP.
Detection of Insider Attacks in Distributed Projected Subgradient Algorithms
Simulation results demonstrate that the proposed AI-based methods are beneficial to improve performance of detecting and localizing malicious agents over score-based methods, and the peer-to-peer neural network model is indeed robust to target issues.
Targeted Physical-World Attention Attack on Deep Learning Models in Road Sign Recognition
To alleviate these problems, this paper proposes the targeted attention attack (TAA) method for real world road sign attack.
When Blockchain Meets AI: Optimal Mining Strategy Achieved By Machine Learning
Experimental results indicate that, without knowing the parameter values of the mining MDP model, our multi-dimensional RL mining algorithm can still achieve the optimal performance over time-varying blockchain networks.
Cryptography and Security
Pre-Processing-Free Gear Fault Diagnosis Using Small Datasets with Deep Convolutional Neural Network-Based Transfer Learning
On the other hand, while the deep neural networks based approaches feature adaptive feature extractions and inherent classifications, they usually require a substantial set of training data and thus hinder their usage for engineering applications with limited training data such as gearbox fault diagnosis.
A wavelet frame coefficient total variational model for image restoration
In this paper, we propose a vector total variation (VTV) of feature image model for image restoration.
