The research on credit card fraud detection can protect consumers and banks from economic losses. The current research direction mainly focuses on improving the efficiency and accuracy of fraud detection using machine...
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Visually impaired individuals face difficulties in public transportation, especially in recognizing bus numbers. Though existing image captioning method can provide some bus scene information via voice broadcasting, p...
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Existing end-to-end quality of service (QoS) prediction methods based on deep learning often use one-hot encodings as features, which are input into neural networks. It is difficult for the networks to learn the infor...
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Creating realistic materials is essential in the construction of immersive virtual *** existing techniques for material capture and conditional generation rely on flash-lit photos,they often produce artifacts when the...
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Creating realistic materials is essential in the construction of immersive virtual *** existing techniques for material capture and conditional generation rely on flash-lit photos,they often produce artifacts when the illumination mismatches the training *** this study,we introduce DiffMat,a novel diffusion model that integrates the CLIP image encoder and a multi-layer,crossattention denoising backbone to generate latent materials from images under various *** a pre-trained StyleGAN-based material generator,our method converts these latent materials into high-resolution SVBRDF textures,a process that enables a seamless fit into the standard physically based rendering pipeline,reducing the requirements for vast computational resources and expansive *** surpasses existing generative methods in terms of material quality and variety,and shows adaptability to a broader spectrum of lighting conditions in reference images.
With the aggressive shrinking of transistor feature sizes, nano-scale CMOS circuits are becoming more vulnerable to multi-node-upsets, e.g., triple-node-upsets (TNUs) as well as quadruple-node-upsets (QNUs), caused by...
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People who have trouble communicating verbally are often dependent on sign language,which can be difficult for most people to understand,making interaction with them a difficult *** Sign Language Recognition(SLR)syste...
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People who have trouble communicating verbally are often dependent on sign language,which can be difficult for most people to understand,making interaction with them a difficult *** Sign Language Recognition(SLR)system takes an input expression from a hearing or speaking-impaired person and outputs it in the form of text or voice to a normal *** existing study related to the Sign Language Recognition system has some drawbacks,such as a lack of large datasets and datasets with a range of backgrounds,skin tones,and *** research efficiently focuses on Sign Language Recognition to overcome previous *** importantly,we use our proposed Convolutional Neural Network(CNN)model,“ConvNeural”,in order to train our ***,we develop our own datasets,“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”,both of which have ambiguous backgrounds.“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”both include images of Bangla characters and numerals,a total of 24,615 and 8437 images,***“ConvNeural”model outperforms the pre-trained models with accuracy of 98.38%for“BdSL_OPSA22_STATIC1”and 92.78%for“BdSL_OPSA22_STATIC2”.For“BdSL_OPSA22_STATIC1”dataset,we get precision,recall,F1-score,sensitivity and specificity of 96%,95%,95%,99.31%,and 95.78%***,in case of“BdSL_OPSA22_STATIC2”dataset,we achieve precision,recall,F1-score,sensitivity and specificity of 90%,88%,88%,100%,and 100%respectively.
Neural networks are widely known to be vulnerable to backdoor attacks, witch are full of threats, a method that poisons a portion of the training data to make the target model perform well on normal data sets, while o...
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With the continuous development and application of unmanned vehicle technology, more and more unmanned vehicles must work in a variety of different bad weather and environmental conditions, which also brings higher re...
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Monocular depth estimation is an important research field in computer vision, with many applications in autonomous driving, 3D reconstruction, and other fields. However, previous research on monocular depth estimation...
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Gait analysis is useful for personal identification in public spaces. Recent, advancements in deep learning technology have enabled highly accurate estimation of human joint positions in images, making practical appli...
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