With the prosperity of the intelligent surveillance, multiple cameras have been applied to localize pedestrians more accurately. However, previous methods rely on laborious annotations of pedestrians in every frame an...
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Given the high annotation costs and ethical considerations associated with medical images, leveraging a limited number of annotated samples for Few-Shot Medical Image Segmentation (FSMIS) has become increasingly preva...
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Stock prices are associated with the dynamic nature of the market;hence it is excruciating to predict the numbers. It has always been tough to invest in a set of assets, the oddity of the financial market does not all...
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The need for a personalized user experience brought recommendation systems to the forefront of digital innovation. However, traditional approaches tend to often forget human emotions, which represent a critical driver...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few meth...
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Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.
AI-empowered automatic driving has experienced rapid development in industrial cyber-physical systems (CPSs), especially in safety vehicles and driverless technologies. 3D object detection is an important task for per...
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Medical image segmentation plays an important role in computer-aid diagnosis. In the past years, convolutional neural networks, especially the UNet-based architectures with symmetric U-shape encoder-decoder structure ...
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In recent years, the increasing number of individuals diagnosed with depression and the growing awareness of its impact on modern society have highlighted the significance of accurate depression diagnosis. Microarray ...
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The unique property of chirality is widely used in various *** the past few decades,a great deal of research has been conducted on the interactions between light and matter,resulting in significant technical advanceme...
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The unique property of chirality is widely used in various *** the past few decades,a great deal of research has been conducted on the interactions between light and matter,resulting in significant technical advancements in the precise manipulation of light field *** this review,which focuses on current chiral optics research,we introduce the fundamental theory of chirality and highlight the latest achievements in enhancing chiral signals through artificial nano-manufacturing technology,with a particular focus on mechanisms such as light scattering and Mie resonance used to amplify chiral *** providing an overview of enhanced chiral signals,this review aims to provide researchers with an indepth understanding of chiral phenomena and its versatile applications in various domains.
Graphics Interchange Format (GIF) encoding is the art of reproducing an image with limited colors. Existing GIF encoding schemes often introduce unpleasant visual artifacts such as banding artifact, dotted-pattern noi...
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