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Pattern Recognition. ICPR International Workshops and Challenges

Virtual Event, January 10–15, 2021, Proceedings, Part I

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Alberto Del Bimbo

    1. Dipartimento di Ingegneria dell’Informazione, University of Firenze, Firenze, Italy

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  2. Rita Cucchiara

    1. Dipartimento di Ingegneria “Enzo Ferrari”, Università di Modena e Reggio Emilia, Modena, Italy

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  3. Stan Sclaroff

    1. Department of Computer Science, Boston University, Boston, USA

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  4. Giovanni Maria Farinella

    1. Dipartimento di Matematica e Informatica, University of Catania, Catania, Italy

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  5. Tao Mei

    1. Cloud & AI, JD.COM, Beijing, China

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  6. Marco Bertini

    1. Dipartimento di Ingegneria dell’Informazione, University of Firenze, Firenze, Italy

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  7. Hugo Jair Escalante

    1. Computational Sciences Department, National Institute of Astrophysics, Optics and Electronics (INAOE), Tonantzintla, Mexico

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  8. Roberto Vezzani

    1. Dipartimento di Ingegneria “Enzo Ferrari”, Università di Modena e Reggio Emilia, Modena, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12661)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: ICPR 2021.

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About this book

This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.

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Keywords

Table of contents (55 papers)

  1. Front Matter

    Pages i-xx
    Download chapter PDF

  2. 3DHU 2020 - 3D Human Understanding

    1. Front Matter

      Pages 1-3
      Download chapter PDF

    2. Subject Identification Across Large Expression Variations Using 3D Facial Landmarks

      • SK Rahatul Jannat, Diego Fabiano, Shaun Canavan, Tempestt Neal
      Pages 5-13

    3. 3D Human Pose Estimation Based on Multi-Input Multi-Output Convolutional Neural Network and Event Cameras: A Proof of Concept on the DHP19 Dataset

      • Alessandro Manilii, Leonardo Lucarelli, Riccardo Rosati, Luca Romeo, Adriano Mancini, Emanuele Frontoni
      Pages 14-25

    4. Image-Based Out-of-Distribution-Detector Principles on Graph-Based Input Data in Human Action Recognition

      • Jens Bayer, David Münch, Michael Arens
      Pages 26-40

    5. A Novel Joint Points and Silhouette-Based Method to Estimate 3D Human Pose and Shape

      • Zhongguo Li, Anders Heyden, Magnus Oskarsson
      Pages 41-56

    6. Pose Based Trajectory Forecast of Vulnerable Road Users Using Recurrent Neural Networks

      • Viktor Kress, Stefan Zernetsch, Konrad Doll, Bernhard Sick
      Pages 57-71

    7. Towards Generalization of 3D Human Pose Estimation in the Wild

      • Renato Baptista, Alexandre Saint, Kassem Al Ismaeil, Djamila Aouada
      Pages 72-81

    8. Space-Time Triplet Loss Network for Dynamic 3D Face Verification

      • Anis Kacem, Hamza Ben Abdesslam, Kseniya Cherenkova, Djamila Aouada
      Pages 82-90

  3. AIDP - Artificial Intelligence for Digital Pathology

    1. Front Matter

      Pages 91-95
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    2. Noise Robust Training of Segmentation Model Using Knowledge Distillation

      • Geetank Raipuria, Saikiran Bonthu, Nitin Singhal
      Pages 97-104

    3. Semi-supervised Learning with a Teacher-Student Paradigm for Histopathology Classification: A Resource to Face Data Heterogeneity and Lack of Local Annotations

      • Niccolò Marini, Sebastian Otálora, Henning Müller, Manfredo Atzori
      Pages 105-119

    4. Self-attentive Adversarial Stain Normalization

      • Aman Shrivastava, William Adorno, Yash Sharma, Lubaina Ehsan, S. Asad Ali, Sean R. Moore et al.
      Pages 120-140

    5. Certainty Pooling for Multiple Instance Learning

      • Jacob Gildenblat, Ido Ben-Shaul, Zvi Lapp, Eldad Klaiman
      Pages 141-153

    6. Classification of Noisy Free-Text Prostate Cancer Pathology Reports Using Natural Language Processing

      • Anjani Dhrangadhariya, Sebastian Otálora, Manfredo Atzori, Henning Müller
      Pages 154-166

    7. AI Slipping on Tiles: Data Leakage in Digital Pathology

      • Nicole Bussola, Alessia Marcolini, Valerio Maggio, Giuseppe Jurman, Cesare Furlanello
      Pages 167-182

  4. AIHA 2020 - International Workshop on Artificial Intelligence for Healthcare Applications

    1. Front Matter

      Pages 183-186
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    2. Predictive Medicine Using Interpretable Recurrent Neural Networks

      • André Ferreira, Sara C. Madeira, Marta Gromicho, Mamede de Carvalho, Susana Vinga, Alexandra M. Carvalho
      Pages 187-202

    3. Automated Detection of Adverse Drug Events from Older Patients’ Electronic Medical Records Using Text Mining

      • Nicola Colic, Patrick Beeler, Chantal Csajka, Vasiliki Foufi, Frederic Gaspar, Marie-Annick Le Pogam et al.
      Pages 203-211

    4. Length of Stay Prediction for Northern Italy COVID-19 Patients Based on Lab Tests and X-Ray Data

      • Mattia Chiari, Alfonso E. Gerevini, Roberto Maroldi, Matteo Olivato, Luca Putelli, Ivan Serina
      Pages 212-226
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Other volumes

  1. Pattern Recognition. ICPR International Workshops and Challenges

  2. Pattern Recognition. ICPR International Workshops and Challenges

  3. Pattern Recognition. ICPR International Workshops and Challenges

  4. Pattern Recognition. ICPR International Workshops and Challenges

  5. Pattern Recognition. ICPR International Workshops and Challenges

  6. Pattern Recognition. ICPR International Workshops and Challenges

  7. Pattern Recognition. ICPR International Workshops and Challenges

  8. Pattern Recognition. ICPR International Workshops and Challenges

Editors and Affiliations

  • Dipartimento di Ingegneria dell’Informazione, University of Firenze, Firenze, Italy

    Alberto Del Bimbo, Marco Bertini

  • Dipartimento di Ingegneria “Enzo Ferrari”, Università di Modena e Reggio Emilia, Modena, Italy

    Rita Cucchiara, Roberto Vezzani

  • Department of Computer Science, Boston University, Boston, USA

    Stan Sclaroff

  • Dipartimento di Matematica e Informatica, University of Catania, Catania, Italy

    Giovanni Maria Farinella

  • Cloud & AI, JD.COM, Beijing, China

    Tao Mei

  • Computational Sciences Department, National Institute of Astrophysics, Optics and Electronics (INAOE), Tonantzintla, Mexico

    Hugo Jair Escalante

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