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Research on Algorithms of Lateral Face Recognition Based on Data Generation

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  1. Chapter and Conference Paper

    Words Can Be Confusing: Stereotype Bias Removal in Text Classification at the Word Level

    Text classification is a widely used task in natural language processing. However, the presence of stereotype bias in text classification can lead to unfair and inaccurate predictions. Stereotype bias is parti...

    Shaofei Shen, Mingzhe Zhang, Weitong Chen in Advances in Knowledge Discovery and Data M… (2023)

  2. Chapter and Conference Paper

    Correction to: Weakly Supervised Whole Cardiac Segmentation via Attentional CNN

    In the originally published version of chapter 9, by error, the author **ye Peng had been assigned affiliation no. “3” instead of “2”. This has been corrected.

    Erlei Zhang, Minghui Sima, Jun Wang, **ye Peng, **glei Li in Intelligence Science IV (2022)

  3. Chapter and Conference Paper

    Correction to: Short Text Clustering with a Deep Multi-embedded Self-supervised Model

    Due to an oversight, the second affiliation of three co-authors was omitted in the originally published version. The revised version has the correct affiliations of all co-authors.

    Kai Zhang, Zheng Lian, Jiangmeng Li in Artificial Neural Networks and Machine Lea… (2021)

  4. Chapter and Conference Paper

    Correction to: A Multiple Encoders Network for Stroke Lesion Segmentation

    The chapter was inadvertently published with missing acknowledgement which has been included.

    **angchen Zhang, Huan Xu, Yujun Liu, Jiajia Liao in Pattern Recognition and Computer Vision (2021)

  5. Chapter and Conference Paper

    Correction to: Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification

    In a former version of this paper, the CERNET Innovation Project (NGII20190621) was missing from the Acknowledgement section. This has been corrected.

    Chunxiang Feng, Biao Jie, **ntao Ding in Machine Learning in Medical Imaging (2020)

  6. Chapter and Conference Paper

    A Novel Method to Solve the Separation Problem of LDA

    Linear discriminant analysis (LDA) is one of the most classical linear projection techniques for feature extraction, widely used in kinds of fields. Classical LDA is contributed to finding an optimal projectio...

    Meng Zhang, Wei Li, Bo Zhang in Intelligent Information Processing X (2020)

  7. Chapter and Conference Paper

    Ballistocardiogram Artifact Removal for Concurrent EEG-fMRI Recordings Using Blind Source Separation Based on Dictionary Learning

    Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have attracted extensive attention and research owing to their high spatial and temporal resolution. Howe...

    Yuxi Liu, Jianhai Zhang, Bohui Zhang, Wanzeng Kong in Intelligent Information Processing X (2020)

  8. Chapter and Conference Paper

    Environmental Parameters Analysis and Power Prediction for Photovoltaic Power Generation Based on Ensembles of Decision Trees

    Due to the influence of solar irradiation, temperature and other environmental factors, the output power of photovoltaic power generation has great randomness and randomness discontinuity. In this paper, a me...

    Shuai Zhang, Hongwei Dai, Aizhou Yang, Zhongzhi Shi in Intelligent Information Processing X (2020)

  9. Chapter and Conference Paper

    A Content-Based Deep Hybrid Approach with Segmented Max-Pooling

    Convolutional matrix factorization (ConvMF), which integrates convolutional neural network (CNN) into probabilistic matrix factorization (PMF), has been recently proposed to utilize the contextual information...

    Dapeng Zhang, Liu Yajun, Jiancheng Liu in Intelligent Information Processing X (2020)

  10. Chapter and Conference Paper

    GAN-Based Method for Synthesizing Multi-focus Cell Images

    This paper presents a method for synthesizing multi-focus cell images by using generative adversarial networks (GANs). The proposed method, called multi-focus image GAN (MI-GAN), consists of two generators. A ...

    Ken’ich Morooka, Xueru Zhang, Shoko Miyauchi, Ryo Kurazume in Image and Video Technology (2020)

  11. Chapter and Conference Paper

    MeshingNet: A New Mesh Generation Method Based on Deep Learning

    We introduce a novel approach to automatic unstructured mesh generation using machine learning to predict an optimal finite element mesh for a previously unseen problem. The framework that we have developed is...

    Zheyan Zhang, Yongxing Wang, Peter K. Jimack, He Wang in Computational Science – ICCS 2020 (2020)

  12. Chapter and Conference Paper

    Ringer: Systematic Mining of Malicious Domains by Dynamic Graph Convolutional Network

    Malicious domains are critical resources in network security, behind which attackers hide malware to launch the malicious attacks. Therefore, blocking malicious domains is the most effective and practical way ...

    Zhicheng Liu, Shuhao Li, Yongzheng Zhang, **aochun Yun in Computational Science – ICCS 2020 (2020)

  13. Chapter and Conference Paper

    Challenge Collapsar (CC) Attack Traffic Detection Based on Packet Field Differentiated Preprocessing and Deep Neural Network

    Distributed Denial of Service (DDoS) attack is one of the top cyber threats. As a kind of application layer DDoS attack, Challenge Collapsar (CC) attack has become a real headache for defenders. However, there...

    **aolin Liu, Shuhao Li, Yongzheng Zhang, **aochun Yun in Computational Science – ICCS 2020 (2020)

  14. Chapter and Conference Paper

    Monolithic Arbitrary Lagrangian–Eulerian Finite Element Method for a Multi-domain Blood Flow–Aortic Wall Interaction Problem

    In this paper, an arbitrary Lagrangian–Eulerian (ALE) finite element method in the monolithic approach is developed for a multi-domain blood flow–aortic wall interaction problem with multiple moving interfaces...

    Pengtao Sun, Chen-Song Zhang, Rihui Lan, Lin Li in Computational Science – ICCS 2020 (2020)

  15. Chapter and Conference Paper

    VisDrone-SOT2018: The Vision Meets Drone Single-Object Tracking Challenge Results

    Single-object tracking, also known as visual tracking, on the drone platform attracts much attention recently with various applications in computer vision, such as filming and surveillance. However, the lack o...

    Longyin Wen, Pengfei Zhu, Dawei Du, **ao Bian in Computer Vision – ECCV 2018 Workshops (2019)

  16. Chapter and Conference Paper

    VisDrone-DET2018: The Vision Meets Drone Object Detection in Image Challenge Results

    Object detection is a hot topic with various applications in computer vision, e.g., image understanding, autonomous driving, and video surveillance. Much of the progresses have been driven by the availability of ...

    Pengfei Zhu, Longyin Wen, Dawei Du, **ao Bian in Computer Vision – ECCV 2018 Workshops (2019)

  17. Chapter and Conference Paper

    The Sixth Visual Object Tracking VOT2018 Challenge Results

    The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers...

    Matej Kristan, Aleš Leonardis, Jiří Matas in Computer Vision – ECCV 2018 Workshops (2019)

  18. Chapter and Conference Paper

    Correction to: Prediction on Payment Volume from Customer Service Electricity Channel

    In the originally published version of chapter 28, the first affiliation included an error. The first affiliation has been corrected from “USA State Grid Corporation Customer Service Center, Tian** 300000, Ch...

    Gong Lihua, Sheng Yan, Liu Kunpeng, Zhu Longzhu in Artificial Intelligence and Security (2019)

  19. Chapter and Conference Paper

    Correction to: Symmetry-Aware Face Completion with Generative Adversarial Networks

    In the original version of this book the address of the author Di Sun was incorrect. This has now been corrected.

    Jiawan Zhang, Rui Zhan, Di Sun, Gang Pan in Computer Vision – ACCV 2018 (2019)

  20. Chapter and Conference Paper

    Correction to: Personalized Travel Recommendation via Multi-view Representation Learning

    In the original version of the paper the author’s name was incorrectly spelled as Bin Han. It has been corrected to Bing Han.

    Yujun Zhang, Bing Han, **nbo Gao, Haoran Li in Pattern Recognition and Computer Vision (2019)

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