The course Introduction to computer Networks (ICN) has become one of the most vital courses in computerscience and softwareengineering degrees and clearly is an imperative course for a degree in computer networking....
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Traditional serial motif mining methods struggle to quickly identify motif information in large-scale time series data. A CUDA-based multidimensional motif mining algorithm is proposed to discover motifs in multidimen...
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Cancer is one of the fatal threats to human beings. However, early detection and diagnosis can significantly reduce death risk, in which cytology classification is indispensable. Researchers have proposed many deep le...
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In large-scale distributed systems, the performance of computation tasks is often significantly degraded by straggling nodes. Recently, coded computation has emerged as a promising approach to mitigate the effect of s...
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This paper introduces a dynamic-frame time division multiple access (DF-TDMA) scheme aimed at decreasing the age of collection (AoC) in collaborative monitoring scenarios. Unlike the conventional age of information (A...
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Semi-supervised-Learning(SSL) providing a solution to leverage vast amounts of unlabeled data. In cognitive psychology, the Primacy-effect refers to the phenomenon where the initial information encountered tends to le...
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With the continuous advancement of the smart home market, household items have become more intelligent. By identifying the different material attributes of various household tabletops, we can obtain contextual informa...
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Melanoma is of the lethal and rare types of skin *** is curable at an initial stage and the patient can survive *** is very difficult to screen all skin lesion patients due to costly *** are requiring a correct method ...
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Melanoma is of the lethal and rare types of skin *** is curable at an initial stage and the patient can survive *** is very difficult to screen all skin lesion patients due to costly *** are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders,pigment networks,and the color of *** challenges are required an automated system to classify the clinical features of melanoma and non-melanoma *** trained clinicians can overcome the issues such as low contrast,lesions varying in size,color,and the existence of several objects like hair,reflections,air bubbles,and oils on almost all *** contour is one of the suitable methods with some drawbacks for the segmentation of irre-gular *** entropy and morphology-based automated mask selection is pro-posed for the active contour *** proposed method can improve the overall segmentation along with the boundary of melanoma *** this study,features have been extracted to perform the classification on different texture scales like Gray level co-occurrence matrix(GLCM)and Local binary pattern(LBP).When four different moments pull out in six different color spaces like HSV,Lin RGB,YIQ,YCbCr,XYZ,and CIE L*a*b then global information from different colors channels have been ***,hybrid fused texture features;such as local,color feature as global,shape features,and Artificial neural network(ANN)as classifiers have been proposed for the categorization of the malignant and *** had been carried out on datasets Dermis,DermQuest,and *** results of our advanced method showed super-iority and contrast with the existing state-of-the-art techniques.
作者:
Ma, HaoYang, JingyuanHuang, HuiShenzhen University
Visual Computing Research Center College of Computer Science and Software Engineering Shenzhen China (GRID:grid.263488.3) (ISNI:0000 0001 0472 9649)
Exemplar-based image translation involves converting semantic masks into photorealistic images that adopt the style of a given ***,most existing GAN-based translation methods fail to produce photorealistic *** this st...
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Exemplar-based image translation involves converting semantic masks into photorealistic images that adopt the style of a given ***,most existing GAN-based translation methods fail to produce photorealistic *** this study,we propose a new diffusion model-based approach for generating high-quality images that are semantically aligned with the input mask and resemble an exemplar in *** proposed method trains a conditional denoising diffusion probabilistic model(DDPM)with a SPADE module to integrate the semantic *** then used a novel contextual loss and auxiliary color loss to guide the optimization process,resulting in images that were visually pleasing and semantically *** demonstrate that our method outperforms state-of-the-art approaches in terms of both visual quality and quantitative metrics.
Sentiment Analysis deals with consumer reviews available on blogs,discussion forums,E-commerce websites,andApp *** online reviews about products are also becoming essential for consumers and companies as *** rely on t...
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Sentiment Analysis deals with consumer reviews available on blogs,discussion forums,E-commerce websites,andApp *** online reviews about products are also becoming essential for consumers and companies as *** rely on these reviews to make their decisions about products and companies are also very interested in these reviews to judge their products and *** reviews are also a very precious source of information for requirement *** companies and consumers are not very satisfied with the overall sentiment;they like fine-grained knowledge about consumer *** to this,many researchers have developed approaches for aspect-based sentiment *** existing approaches concentrate on explicit aspects to analyze the sentiment,and only a few studies rely on capturing implicit *** paper proposes a Keywords-Based Aspect Extraction method,which captures both explicit and implicit *** also captures opinion words and classifies the sentiment about each *** applied semantic similarity-basedWordNet and SentiWordNet lexicon to improve aspect *** used different collections of customer reviews for experiment purposes,consisting of eight datasets over seven *** compared our approach with other state-of-the-art approaches,including Rule Selection using Greedy Algorithm(RSG),Conditional Random Fields(CRF),Rule-based Extraction(RubE),and Double Propagation(DP).Our results have shown better performance than all of these approaches.
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