Stress, particularly learning stress, is prevalent among Chinese elementary school children and can lead to severe health and psychological consequences. Unlike adults, these children often lack the self-awareness to ...
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Augmented Reality (AR) for interactive entertainment is exploring the potential of open space and multiplayer synchronization to expand user experience on mobile devices. However, complex interaction problems have hin...
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Reconstructing high-fidelity hand models with intricate textures plays a crucial role in enhancing human-object interaction and advancing real-world applications. Despite the state-of-the-art methods excelling in text...
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Despite large language models (LLMs) have demonstrated impressive performance in various tasks, they are still suffering from the factual inconsistency problem called hallucinations. For instance, LLMs occasionally ge...
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Recently, audio-visual speech recognition has attracted increasing attention. However, most existing works only focused on scenarios with two speakers. In this work, we study the effect of speaker number in AVSR task ...
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How to use mediated technology helping people regulate emotion is a popular topic in HCI community. Using Haptic instead of other sensory stimuli becomes a new trend. In this paper, we present WindCheck, a wearable de...
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The rapid development of new energy vehicles and 5G communication technologies has led to higher demands for the safety,energy density,and cycle performance of lithium-ion batteries as power ***,the currently used liq...
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The rapid development of new energy vehicles and 5G communication technologies has led to higher demands for the safety,energy density,and cycle performance of lithium-ion batteries as power ***,the currently used liquid carbonate compounds in commercial lithium-ion battery electrolytes pose potential safety hazards such as leakage,swelling,corrosion,and *** electrolytes can be used to mitigate these risks and create a safer lithium ***,high-energy density can be achieved by using solid electrolytes along with high-voltage cathode and metal lithium *** types of solid electrolytes are generally used:inorganic solid electrolytes and polymer solid *** solid electrolytes have high ionic conductivity,electrochemical stability window,and mechanical strength,but suffer from large solid/solid contact resistance between the electrode and *** solid electrolytes have good flexibility,processability,and contact interface properties,but low room temperature ionic conductivity,necessitating operation at elevated *** solid electrolytes(CSEs) are a promising alternative because they offer light weight and flexibility,like polymers,as well as the strength and stability of inorganic *** paper presents a comprehensive review of recent advances in CSEs to help researchers optimize CSE composition and interactions for practical *** covers the development history of solid-state electrolytes,CSE properties with respect to nanofillers,morphology,and polymer types,and also discusses the lithium-ion transport mechanism of the composite electrolyte,and the methods of engineering interfaces with the positive and negative ***,the paper aims to provide an outlook on the potential applications of CSEs in solid-state lithium batteries,and to inspire further research aimed at the development of more systematic optimization strategies for CSEs.
The effectiveness of modeling contextual information has been empirically shown in numerous computer vision tasks. In this paper, we propose a simple yet efficient augmented fully convolutional network(AugFCN) by aggr...
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The effectiveness of modeling contextual information has been empirically shown in numerous computer vision tasks. In this paper, we propose a simple yet efficient augmented fully convolutional network(AugFCN) by aggregating content-and position-based object contexts for semantic ***, motivated because each deep feature map is a global, class-wise representation of the input,we first propose an augmented nonlocal interaction(AugNI) to aggregate the global content-based contexts through all feature map interactions. Compared to classical position-wise approaches, AugNI is more efficient. Moreover, to eliminate permutation equivariance and maintain translation equivariance, a learnable,relative position embedding branch is then supportably installed in AugNI to capture the global positionbased contexts. AugFCN is built on a fully convolutional network as the backbone by deploying AugNI before the segmentation head network. Experimental results on two challenging benchmarks verify that AugFCN can achieve a competitive 45.38% mIoU(standard mean intersection over union) and 81.9% mIoU on the ADE20K val set and Cityscapes test set, respectively, with little computational overhead. Additionally, the results of the joint implementation of AugNI and existing context modeling schemes show that AugFCN leads to continuous segmentation improvements in state-of-the-art context modeling. We finally achieve a top performance of 45.43% mIoU on the ADE20K val set and 83.0% mIoU on the Cityscapes test set.
As age advances, the decline in bodily functions and the rise in age-related diseases pose various challenges to the daily lives of the older population. This scoping review discusses the potential of Electromyography...
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In recent years,Transformer has achieved remarkable results in the field of computer vision,with its built-in attention layers effectively modeling global dependencies in images by transforming image features into tok...
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In recent years,Transformer has achieved remarkable results in the field of computer vision,with its built-in attention layers effectively modeling global dependencies in images by transforming image features into token ***,Transformers often face high computational costs when processing large-scale image data,which limits their feasibility in real-time *** address this issue,we propose Token Masked Pose Transformers(TMPose),constructing an efficient Transformer network for pose *** network applies semantic-level masking to tokens and employs three different masking strategies to optimize model performance,aiming to reduce computational *** results show that TMPose reduces computational complexity by 61.1%on the COCO validation dataset,with negligible loss in ***,our performance on the MPII dataset is also *** research not only enhances the accuracy of pose estimation but also significantly reduces the demand for computational resources,providing new directions for further studies in this field.
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