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Advances in Computer Vision

Proceedings of the 2019 Computer Vision Conference (CVC), Volume 1

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Kohei Arai

    1. Saga University, Saga, Japan

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    You can also search for this editor in PubMed   Google Scholar

  2. Supriya Kapoor

    1. The Science and Information (SAI) Organization, Bradford, UK

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    You can also search for this editor in PubMed   Google Scholar

  • Presents the latest research on computer vision
  • Gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019
  • Written by respected experts in the field

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 943)

Included in the following conference series:

Conference proceedings info: CVC 2019.

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Table of contents (59 papers)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Deep Learning for Detection of Railway Signs and Signals

    • Georgios Karagiannis, Søren Olsen, Kim Pedersen
    Pages 1-15

  3. 3D Conceptual Design Using Deep Learning

    • Zhangsihao Yang, Haoliang Jiang, Lan Zou
    Pages 16-26

  4. The Effect of Color Channel Representations on the Transferability of Convolutional Neural Networks

    • Javier Diaz-Cely, Carlos Arce-Lopera, Juan Cardona Mena, Lina Quintero
    Pages 27-38

  5. Weakly Supervised Deep Metric Learning for Template Matching

    • Davit Buniatyan, Sergiy Popovych, Dodam Ih, Thomas Macrina, Jonathan Zung, H. Sebastian Seung
    Pages 39-58

  6. Nature Inspired Meta-heuristic Algorithms for Deep Learning: Recent Progress and Novel Perspective

    • Haruna Chiroma, Abdulsalam Ya’u Gital, Nadim Rana, Shafi’i M. Abdulhamid, Amina N. Muhammad, Aishatu Yahaya Umar et al.
    Pages 59-70

  7. Transfer Probability Prediction for Traffic Flow with Bike Sharing Data: A Deep Learning Approach

    • Wenwen Tu, Hengyi Liu
    Pages 71-85

  8. CanvasGAN: A Simple Baseline for Text to Image Generation by Incrementally Patching a Canvas

    • Amanpreet Singh, Sharan Agrawal
    Pages 86-98

  9. Unsupervised Dimension Reduction for Image Classification Using Regularized Convolutional Auto-Encoder

    • Chaoyang Xu, Ling Wu, Shiping Wang
    Pages 99-108

  10. ISRGAN: Improved Super-Resolution Using Generative Adversarial Networks

    • Vishal Chudasama, Kishor Upla
    Pages 109-127

  11. Deep Learning vs. Traditional Computer Vision

    • Niall O’Mahony, Sean Campbell, Anderson Carvalho, Suman Harapanahalli, Gustavo Velasco Hernandez, Lenka Krpalkova et al.
    Pages 128-144

  12. Self-localization from a 360-Degree Camera Based on the Deep Neural Network

    • Shintaro Hashimoto, Kosuke Namihira
    Pages 145-158

  13. Deep Cross-Modal Age Estimation

    • Ali Aminian, Guevara Noubir
    Pages 159-177

  14. Multi-stage Reinforcement Learning for Object Detection

    • Jonas König, Simon Malberg, Martin Martens, Sebastian Niehaus, Artus Krohn-Grimberghe, Arunselvan Ramaswamy
    Pages 178-191

  15. Road Weather Condition Estimation Using Fixed and Mobile Based Cameras

    • Koray Ozcan, Anuj Sharma, Skylar Knickerbocker, Jennifer Merickel, Neal Hawkins, Matthew Rizzo
    Pages 192-204

  16. Robust Pedestrian Detection Based on Parallel Channel Cascade Network

    • Jiaojiao He, Yongping Zhang, Tuozhong Yao
    Pages 205-221

  17. Novel Scheme for Image Encryption and Decryption Based on a Hermite-Gaussian Matrix

    • Mohammed Alsaedi
    Pages 222-236

  18. MAP Interpolation of an Ising Image Block

    • Matthew G. Reyes, David L. Neuhoff, Thrasyvoulos N. Pappas
    Pages 237-256

  19. Volumetric Data Exploration with Machine Learning-Aided Visualization in Neutron Science

    • Yawei Hui, Yaohua Liu
    Pages 257-271

  20. License Plate Character Recognition Using Binarization and Convolutional Neural Networks

    • Sandeep Angara, Melvin Robinson
    Pages 272-283
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Other volumes

  1. Intelligent Systems in Science and Information 2014

  2. Advances in Computer Vision

  3. Advances in Computer Vision

Keywords

About this book

This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 120 (including 7 poster papers) were selected for inclusion in these proceedings.

The book’s goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science,Image Processing, Deep Learning, and Computer Vision Applications.

Editors and Affiliations

  • Saga University, Saga, Japan

    Kohei Arai

  • The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

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