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Results for “"Xin Yao"”

16+ results

MWMOTE--Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learning

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Sukarna Barua, Md. Monirul Islam, Xin Yao, Kazuyuki Murase

Journal: IEEE Transactions on Knowledge and Data EngineeringYear: 2012Citations: 1141

Imbalanced learning problems contain an unequal distribution of data samples among different classes and pose a challenge to any classifier as it becomes hard to learn the minority class samples. Synthetic oversampling methods address this problem by generating the synthetic minority class samples t...

Physical SciencesComputer ScienceArtificial Intelligence
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Epitaxial growth of wafer-scale molybdenum disulfide semiconductor single crystals on sapphire

Verified

Taotao Li, Wei Guo, Liang Ma, Weisheng Li et al.

Journal: Nature NanotechnologyYear: 2021Citations: 784

Two-dimensional (2D) semiconductors, in particular transition metal dichalcogenides (TMDCs), have attracted great interest in extending Moore's law beyond silicon 1-3 . However, despite extensive efforts 4-25 , the growth of wafer-scale TMDC single crystals on scalable and industry-compatible substr...

Physical SciencesMaterials ScienceMaterials Chemistry
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Gaussian Temporal Awareness Networks for Action Localization

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Fuchen Long, Ting Yao, Zhaofan Qiu, Xinmei Tian et al.

Year: 2019Citations: 382

Temporally localizing actions in a video is a fundamental challenge in video understanding. Most existing approaches have often drawn inspiration from image object detection and extended the advances, e.g., SSD and Faster R-CNN, to produce temporal locations of an action in a 1D sequence. Neverthele...

Physical SciencesComputer ScienceComputer Vision and Pattern Recognition
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Exploring Object Relation in Mean Teacher for Cross-Domain Detection

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Qi Cai, Yingwei Pan, Chong‐Wah Ngo, Xinmei Tian et al.

Year: 2019Citations: 356

Rendering synthetic data (e.g., 3D CAD-rendered images) to generate annotations for learning deep models in vision tasks has attracted increasing attention in recent years. However, simply applying the models learnt on synthetic images may lead to high generalization error on real images due to doma...

Physical SciencesComputer ScienceArtificial Intelligence
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Learning Spatio-Temporal Representation With Local and Global Diffusion

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Zhaofan Qiu, Ting Yao, Chong‐Wah Ngo, Xinmei Tian et al.

Year: 2019Citations: 217

Convolutional Neural Networks (CNN) have been regarded as a powerful class of models for visual recognition problems. Nevertheless, the convolutional filters in these networks are local operations while ignoring the large-range dependency. Such drawback becomes even worse particularly for video reco...

Physical SciencesComputer ScienceComputer Vision and Pattern RecognitionOpen Access
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MXenes for Solar Cells

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Lujie Yin, Yingtao Li, Xincheng Yao, Yanzhou Wang et al.

Journal: Nano-Micro LettersYear: 2021Citations: 211

Abstract Application of two-dimensional MXene materials in photovoltaics has attracted increasing attention since the first report in 2018 due to their metallic electrical conductivity, high carrier mobility, excellent transparency, tunable work function and superior mechanical property. In this rev...

Physical SciencesMaterials ScienceMaterials ChemistryOpen Access
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Mechanism insights and therapeutic intervention of tumor metastasis: latest developments and perspectives

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Xiaoli Shi, Xinyi Wang, Wentao Yao, Dong-Min Shi et al.

Journal: Signal Transduction and Targeted TherapyYear: 2024Citations: 198

Metastasis remains a pivotal characteristic of cancer and is the primary contributor to cancer-associated mortality. Despite its significance, the mechanisms governing metastasis are not fully elucidated. Contemporary findings in the domain of cancer biology have shed light on the molecular aspects ...

Life SciencesBiochemistry, Genetics and Molecular BiologyBiotechnologyOpen Access
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Clinical application and detection techniques of liquid biopsy in gastric cancer

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Shuo Ma, Meiling Zhou, Yanhua Xu, Xinliang Gu et al.

Journal: Molecular CancerYear: 2023Citations: 180

Gastric cancer (GC) is one of the most common tumors worldwide and the leading cause of tumor-related mortality. Endoscopy and serological tumor marker testing are currently the main methods of GC screening, and treatment relies on surgical resection or chemotherapy. However, traditional examination...

Life SciencesBiochemistry, Genetics and Molecular BiologyCancer ResearchOpen Access
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A cohort study of cancer among benzene-exposed workers in China: Overall results

Verified

Song-Nian Yin, Richard B. Hayes, Martha S. Linet, Guilan Li et al.

Journal: American Journal of Industrial MedicineYear: 1996Citations: 153

A large cohort study of 74,828 benzene-exposed and 35,805 unexposed workers employed between 1972 and 1987 in 12 cities in China were followed to determine mortality from all causes and the incidence of lymphohematopoietic malignancies and other hematologic disorders. Benzene-exposed study subjects ...

Life SciencesBiochemistry, Genetics and Molecular BiologyCancer Research
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Evolving artificial neural network ensembles

Verified

Xin Yao, Md. Monirul Islam

Journal: IEEE Computational Intelligence MagazineYear: 2008Citations: 127

Using a coordinated group of simple solvers to tackle a complex problem is not an entirely new idea. Its root could be traced back hundreds of years ago when ancient Chinese suggested a team approach to problem solving. For a long time, engineers have used the divide-and-conquer strategy to decompos...

Physical SciencesComputer ScienceArtificial Intelligence
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A New Adaptive Merging and Growing Algorithm for Designing Artificial Neural Networks

Verified

Md. Tariqul Islam, Abdus Sattar, Falamaki Amin, Xin Yao et al.

Journal: IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)Year: 2009Citations: 122

This paper presents a new algorithm, called adaptive merging and growing algorithm (AMGA), in designing artificial neural networks (ANNs). This algorithm merges and adds hidden neurons during the training process of ANNs. The merge operation introduced in AMGA is a kind of a mixed mode operation, wh...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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Satellite-based ground PM2.5 estimation using a gradient boosting decision tree

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Tianning Zhang, Weihuan He, Hui Zheng, Yaoping Cui et al.

Journal: ChemosphereYear: 2020Citations: 118

Fine particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) is one of the major air pollutants risks to human health worldwide. Satellite-based aerosol optical depth (AOD) products are an effective metric for acquiring PM2.5 information, featuring broad coverage and high resolution...

Physical SciencesEnvironmental ScienceHealth, Toxicology and Mutagenesis
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Silk Fibroin and Sericin Differentially Potentiate the Paracrine and Regenerative Functions of Stem Cells Through Multiomics Analysis

Verified

Yanan Zhang, Renwang Sheng, Jialin Chen, Hongmei Wang et al.

Journal: Advanced MaterialsYear: 2023Citations: 117

Silk fibroin (SF) and sericin (SS), the two major proteins of silk, are attractive biomaterials with great potential in tissue engineering and regenerative medicine. However, their biochemical interactions with stem cells remain unclear. In this study, multiomics are employed to obtain a global view...

Physical SciencesMaterials ScienceBiomaterials
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Highly Compact Artificial Memristive Neuron with Low Energy Consumption

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Yishu Zhang, Wei He, Yujie Wu, Kejie Huang et al.

Journal: SmallYear: 2018Citations: 117

Neuromorphic systems aim to implement large-scale artificial neural network on hardware to ultimately realize human-level intelligence. The recent development of nonsilicon nanodevices has opened the huge potential of full memristive neural networks (FMNN), consisting of memristive neurons and synap...

Physical SciencesEngineeringElectrical and Electronic Engineering
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Plasmonic trimers designed as SERS-active chemical traps for subtyping of lung tumors

Verified

Xing Zhao, Xiaojing Liu, Dexiang Chen, Guodong Shi et al.

Journal: Nature CommunicationsYear: 2024Citations: 102

Abstract Plasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the ‘hotspots’, which account for ≈ 1% o...

Physical SciencesMaterials ScienceElectronic, Optical and Magnetic MaterialsOpen Access
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