Self-supervised emotion recognition leveraging skeleton-based data offers a promising approach for classifying emotional expressions within the extensive amount of unlabeled data gathered by sensors in the Internet of...
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Self-supervised emotion recognition leveraging skeleton-based data offers a promising approach for classifying emotional expressions within the extensive amount of unlabeled data gathered by sensors in the Internet of Things (IoT). Recent advancements in this field have been driven by contrastive learning-based or generative learning-based self-supervised methods, which effectively tackle the issue of sparsely labeled data. In emotion recognition tasks, the emotional high-level semantics embedded in the skeleton data are more important than the subtle joint movements. Compared to existing methods, discrete label prediction can encourage SSL models to abstract high-level semantics in a manner similar to human perception. However, it is challenging to comprehensively capture emotional expressed in skeleton data solely from joint-based features. Moreover, emotional information conveyed through body movements may include redundant details that hinder the understanding of emotional expression. To overcome these challenges, we propose a novel discrete-label-based emotion recognition framework named the Appendage-Informed redundancy-ignoring (AIR) discrete label framework. First, we introduce the Appendage-Skeleton Partitioning (ASP) module, which leverages limb movement data from the original skeleton to explore emotional expression. Next, we propose the Appendage-refined Multi-scale Discrete Label (AMDL) module, which transforms traditional self-supervised tasks into classification tasks. This design continuously extracts emotional semantics from skeleton data during pre-training, functioning similarly to predicting categories and subsequently classifying samples. To further reduce the nonessential information in skeleton data that may negatively impact the generation of accurate emotional categories, we propose the Appendage Label Refinement (ALR) module. It refines the generated categories by using the relationships between the skeleton and the various appendages obtai
In this paper, the problem of joint transmission and computation resource allocation for a multi-user probabilistic semantic communication (PSC) network is investigated. In the considered model, users employ semantic ...
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ISBN:
(数字)9798350304053
ISBN:
(纸本)9798350304060
In this paper, the problem of joint transmission and computation resource allocation for a multi-user probabilistic semantic communication (PSC) network is investigated. In the considered model, users employ semantic information extraction techniques to compress their large-sized raw data before transmitting them to a multi-antenna base station (BS). Our model represents the raw data through comprehensive knowledge graphs, utilizing shared probability graphs between users and the BS for efficient semantic compression. The resource allocation problem is formulated as an optimization problem with the objective of maximizing the sum of equivalent rate of all users, considering total power budget constraint. This joint optimization problem inherently addresses the delicate balance between transmission efficiency and computational complexity. To address this optimization challenge, we present an iterative algorithm in which the optimal solution for the semantic compression ratio of a specific user is determined at each iteration. Numerical results validate the effectiveness of the proposed scheme.
Perceptual quality assessment has always been challenging due to the difficulty in modeling the no-linear human visual system. With the diversity in the contents of multimedia signals, the conventional methods for tra...
Perceptual quality assessment has always been challenging due to the difficulty in modeling the no-linear human visual system. With the diversity in the contents of multimedia signals, the conventional methods for traditional media seems no longer satisfying. One of these emerging media, is the screen content images/videos (SCINs), Containing texts and computer generated graphics, SCVs cannot be sufficiently expressed with features designed for natural sceneries. Therefore, new researches tried to devise objective quality assessment metrics, specificly for screen contents. Recently, a dataset was proposed for quality assessment of screen content videos. Since screen contents are full of structures that spread in cardinal directions, we were motivated to employ the horizontal and vertical subbands of the wavelet transform to characterize these types of visual contents. The features were incorporated in a full-reference method that showed promising results on the publicly available dataset for SCV quality assessment. The method can bo accessed via: https://***/motamedNia/QASCV.
The collaboration of computing powers (CPs) among unmanned aerial vehicles (UAVs)-mounted edge servers is essential to handle data-intensive tasks of user equipments (UEs). This paper presents a multi-UAV computing po...
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In this paper, we introduce a novel uplink semantic relay (SemRelay)-aided wireless communication system, catering to multiple users by leveraging a shared probability graph between the SemRelay and the base station (...
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ISBN:
(数字)9781728190549
ISBN:
(纸本)9781728190556
In this paper, we introduce a novel uplink semantic relay (SemRelay)-aided wireless communication system, catering to multiple users by leveraging a shared probability graph between the SemRelay and the base station (BS). In this system, users transmit text information to the SemRelay through conventional bit transmission, and the SemRelay compresses this information using a knowledge based characterized by probability graph before transmitting it to the BS through semantic communication. Then, the BS recovers the information based on the shared probability graph. While the semantic information compression incurs computational resource consumption, it significantly reduces communication resource usage. This paper addresses the challenge of minimizing overall system latency through jointly optimizing communication and computation re-source allocation, considering limited wireless resources and the system's energy budget. To address this problem, we introduce an efficient iterative algorithm, which employs block coordinate descent for communication resource allocation and exhaustive searching for determining the optimal data compression scheme. In particular, both power allocation subproblem and bandwidth allocation subproblem are proved to be convex. The complexity analysis of the proposed algorithm are also provided. Numerical results validate the effectiveness of the proposed algorithm and the superior performance of semantic communication compared to the conventional bit transmission.
This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the ...
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Space-air-ground integrated networks (SAGINs) are emerging as a pivotal element in the evolution of future wireless networks. Despite their potential, the joint design of communication and computation within SAGINs re...
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作者：
Ahmed, SajibMekhilef, SaadMubin, MarizanTey, Kok SoonRawa, MuhyaddinUniversity of Malaya
Power Electronics and Renewable Energy Research Laboratory Faculty of Engineering Department of Electrical Engineering Kuala Lumpur50603 Malaysia School of Science
Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia University of Malaya
Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia King Abdulaziz University
Center of Research Excellence in Renewable Energy and Power Systems Jeddah21589 Saudi Arabia
Solar energy is considered one of the best essential energy sources to solve the present power crisis. The solar photovoltaic system has a low conversion efficiency that inflicts maximum power extractions. The non-lin...
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Visualizations have played a crucial role in helping quantum computing users explore quantum states in various quantum computing applications. Among them, Bloch Sphere is the widely-used visualization for showing quan...
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