Histological image classification plays a crucial role in cancer diagnosis. However, the acquisition of well-labeled histological images is prohibitively expensive, and obtaining rare abnormal samples is challenging. ...
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ISBN:
(纸本)9798350358780
Histological image classification plays a crucial role in cancer diagnosis. However, the acquisition of well-labeled histological images is prohibitively expensive, and obtaining rare abnormal samples is challenging. Therefore, applying few-shot learning methods to histological image classification tasks holds significant clinical value. Nevertheless, existing research predom-inantly relies on coarse-grained image classification approaches based on natural image datasets, which struggle to address the fine-grained challenges encountered in histological image classification, such as intra-class diversity and inter-class similarity. To tackle this issue, this study proposes a novel few-shot fine-grained classification method for histological images, named 'Category-Aware Feature Map Reconstruction Network.' This method employs channel weights to localize the differences between inter-class and intra-class regions, composed of intra-class channel weights and inter-class channel weights, collectively referred to as category-aware weights. Specifically, intra-class channel weights indicate the matching degree of salient regions within the support set of a particular class, while inter-class channel weights represent the degree of containing distinct information between classes. The category-aware weights are utilized to transform the support feature maps and query feature maps, generating feature maps that capture differentiating details between categories. Finally, the distance between the transformed query feature map and support feature map is calculated to achieve probabilistic predictions for the categories. On a histological few-shot dataset, this method achieves an accuracy of 90.23% using ResNet-12 as the feature extractor, surpassing the baseline model by 5.24% and outperforming other few-shot methods by at least 10% in the 5-way 10-shot experimental setting. The proposed method exhibits exceptional performance on histological image few-shot datasets, playing a
The satisfiability(SAT) problem is an important problem of automated reasoning. In the past decades, many methods of SAT are proposed, such as method based on resolution, method based on tableau and method based on ex...
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The rapid developments of chip-based technology have greatly improved human genetics and made routine the access of thousands of single nucleotide polymorphisms (SNPs) contributing to an informatics challenge. The cha...
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ISBN:
(纸本)9781450328104
The rapid developments of chip-based technology have greatly improved human genetics and made routine the access of thousands of single nucleotide polymorphisms (SNPs) contributing to an informatics challenge. The characterization and interpretation of genes and gene-gene interactions that affect the susceptibility of common, complex multifactorial diseases is a computational and statistical challenge in genome-wide association studies (GWAS). Various methods have been proposed, but they have dificulty to be directly applied to GWAS caused by excessive search space and intensive computational burden. In this paper, we propose an ant colony optimization (ACO) based algorithm by combining the pheromone updating rule with the heuristic information. We tested power performance of our algorithm by conducting suficient experiments including a wide range of simulated datasets experiments and a real genome-wide dataset experiment. Experimental results demonstrate that our algorithm is time efficient and gain good performance in the term of the power of prediction accuracy. Copyright 2014 ACM.
The past decade has witnessed the rapid development of search engines, which has become an indispensable part of everyday life. However, people are no longer satisfied with accessing to ordinary information, and they ...
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In this paper,for a zero-dimensional polynomial ideal I,the authors prove that k[x_(1),x_(2),…,x_(n)]/I is cyclic if and only if the breadth of I is 0 or ***,the authors present a new algorithm to compute polynomial ...
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In this paper,for a zero-dimensional polynomial ideal I,the authors prove that k[x_(1),x_(2),…,x_(n)]/I is cyclic if and only if the breadth of I is 0 or ***,the authors present a new algorithm to compute polynomial univariate representation(PUR)of such an ideal.
In recent years, with the development of the wireless sensor networks, the localization method receives the attention of many researchers. However, due to the network cost and characteristics of sensor nodes, most of ...
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Dynamic Bayesian Network (DBN) is a graphical model for representing temporal stochastic processes. Learning the structure of DBN is a fundamental step for parameter learning, inference and application. For large scal...
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The configuration problem in manufacture is more complicated than most other fields. Therefore, the design of modeling and reasoning module for product configuration manager in manufacture is very important and comple...
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The workflow model is the abstract expression of the workflow or the business process. Following the WfMC reference model, a PKI-based lightweight workflow model named as PBLW is put forward in this paper. The framewo...
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Mobile ambients is a process calculus for modeling mobile agents in wide-area networks. It has important theoretical and practical values in studying concurrent and mobile computation as well as the security of intera...
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