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Found 16 papers, 1 papers with code
360SFUDA++: Towards Source-free UDA for Panoramic Segmentation by Learning Reliable Category Prototypes
However, as the distinct projections make it less possible to directly transfer knowledge between domains, we then propose Reliable Panoramic Prototype Adaptation Module (RP2AM) to transfer knowledge at both prediction and prototype levels.
Unsupervised Visible-Infrared ReID via Pseudo-label Correction and Modality-level Alignment
Specifically, to address the first challenge, we propose a pseudo-label correction strategy that utilizes a Beta Mixture Model to predict the probability of mis-clustering based network's memory effect and rectifies the correspondence by adding a perceptual term to contrastive learning.
Semantics, Distortion, and Style Matter: Towards Source-free UDA for Panoramic Segmentation
However, the distinct projection discrepancies between source and target domains impede the direct knowledge transfer; thus, we propose a panoramic prototype adaptation module (PPAM) to integrate panoramic prototypes from the extracted knowledge for adaptation.
ClassLIE: Structure- and Illumination-Adaptive Classification for Low-Light Image Enhancement
A class prediction block is then designed to classify the degradation information by calculating the structure similarity scores on the reflectance map and mean square error on the illumination map.
BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models
Moreover, the content generated by LLMs is difficult to identify and trace, and it is difficult to cross-platform mutual recognition.
Generative Pre-trained Transformer: A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions
GPT is based on the transformer architecture, a deep neural network designed for natural language processing tasks.
360$^\circ$ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer
Our key idea is to transfer the scene structural knowledge from the HR image modality and the corresponding LR depth maps to achieve the goal of HR depth estimation without any extra inference cost.
Auction Based Clustered Federated Learning in Mobile Edge Computing System
In recent years, mobile clients' computing ability and storage capacity have greatly improved, efficiently dealing with some applications locally.
DynaComm: Accelerating Distributed CNN Training between Edges and Clouds through Dynamic Communication Scheduling
To reduce uploading bandwidth and address privacy concerns, deep learning at the network edge has been an emerging topic.
Leveraging AI and Intelligent Reflecting Surface for Energy-Efficient Communication in 6G IoT
The ever-increasing data traffic, various delay-sensitive services, and the massive deployment of energy-limited Internet of Things (IoT) devices have brought huge challenges to the current communication networks, motivating academia and industry to move to the sixth-generation (6G) network.
Collaborative Three-Tier Architecture Non-contact Respiratory Rate Monitoring using Target Tracking and False Peaks Eliminating Algorithms
We proposed a non-contact respiratory rate monitoring system with a cooperative three-layer design to increase the precision of respiratory monitoring and decrease data transmission latency.
Deep Direct Visual Odometry
Extensive experiments on the KITTI dataset show that the proposed constraints can effectively improve the scale-consistency of TrajNet when compared with previous unsupervised monocular methods, and integration with TrajNet makes the initialization and tracking of DSO more robust and accurate.
Big Data Analytics for Large Scale Wireless Networks: Challenges and Opportunities
We then present a detailed survey of the technical solutions to the challenges in BDA for large scale wireless networks according to each stage in the life cycle of BDA.
Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics
In recent years, analyzing task-based fMRI (tfMRI) data has become an essential tool for understanding brain function and networks.
Robust Order Scheduling in the Fashion Industry: A Multi-Objective Optimization Approach
In the fashion industry, order scheduling focuses on the assignment of production orders to appropriate production lines.
Differential Evolution with Event-Triggered Impulsive Control
In this paper, an event-triggered impulsive control scheme (ETI) is introduced to improve the performance of DE.
