Journal of Electrical and Electronic Engineering

Special Issue

Learning from Weakly or Webly Supervised Data

  • Submission Deadline: Jan. 15, 2020
  • Status: Submission Closed
  • Lead Guest Editor: Yazhou Yao
About This Special Issue
In the past few years, labeled image datasets have played a critical role in high-level image understanding. For example, ImageNet has acted as one of the most important factors in the recent advance of developing and deploying visual representation learning models. However, the process of constructing ImageNet is both time-consuming and labor-intensive. To reduce the time and labor costs of manual annotation, some works also focused on weakly supervised learning. To further reduce the cost of manual annotation, learning directly from the web data has attracted more and more people's attention. Compared to manual-labeled image datasets, web images are a rich and free resource. For arbitrary categories, the potential training data can be easily obtained from the image search engines like Google or Bing. Unfortunately, due to the error index of the image search engine, the precision of returned images from an image search engine is still unsatisfactory. Original research papers are solicited in any aspect of weakly supervised or webly-supervised learning are welcome.
Aims and Scope:
  1. Weakly supervised learning
  2. Webly supervised learning
  3. Image classification
  4. Object detection
  5. Deep convolutional neural networks
  6. Clustering based methods
Lead Guest Editor
  • Yazhou Yao

    Computer Vision Research Group, Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

Guest Editors
  • Jian Zhang

    Global Big Data Technologies Center, University of Technology Sydney, Sydney, Australia

  • Jun Li

    Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, United States

  • Jingsong Xu

    Global Big Data Technologies Center, University of Technology Sydney, Sydney, Australia

  • Fang Zhao

    Computer Vision Research Group, Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

  • Guosen Xie

    Computer Vision Research Group, Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

  • Lizhong Ding

    Computer Vision Research Group, Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

  • Tianfei Zhou

    Computer Vision Research Group, Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

  • Mamta Yadav

    Department of Computing Sciences, Texas A&M University-Corpus Christi, Corpus Christi, United States

  • Fumin Shen

    School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

  • Fengchao Xiong

    College of Computer Science, Zhejiang University, Hangzhou, China

  • Xiangbo Shu

    School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

  • Elemasetty Uday Kiran

    Department of Electrical and Electronics,Space Development Nexus,Center for Isro Gnss Studies, Hyderabad, India

  • Sankhanil Dey

    Institute of Radio Physics and Electronics, University of Calcutta, Kolkata, India