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Andrew D. Bagdanov

Andrew D. Bagdanov

D-Index & Metrics

Computer Science

D-Index
35
Citations
8053
World Ranking
11479
National Ranking
376

Overview

Andrew D. Bagdanov is affiliated with the University of Florence in Italy. Their research spans the field of computer science, with a particular focus on artificial intelligence and computer vision.

The scientist has contributed to various subfields of study, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Sociology and Political Science
  • Cancer Research

Their recent published papers include:

  • Class-Incremental Learning: Survey and Performance Evaluation on Image Classification, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Class-incremental learning: survey and performance evaluation on image classification, 2020, arXiv (Cornell University)
  • Bottom-up and Layerwise Domain Adaptation for Pedestrian Detection in Thermal Images, 2021, ACM Transactions on Multimedia Computing Communications and Applications
  • Visual Question Answering for Cultural Heritage, 2020, IOP Conference Series Materials Science and Engineering
  • Continually Learning Self-Supervised Representations with Projected Functional Regularization, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Frequent coauthors collaborating with Andrew D. Bagdanov include:

  • Joost van de Weijer
  • Bartłomiej Twardowski
  • Alessandro Sestini
  • Xialei Liu
  • Simone Magistri

The scientist has published in several venues, with the most frequent being:

  • arXiv (Cornell University)
  • 2021 IEEE Conference on Games (CoG)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • ACM Transactions on Multimedia Computing Communications and Applications
  • IOP Conference Series Materials Science and Engineering

The main topics covered in their research work include:

  • Domain Adaptation and Few-Shot Learning
  • Artificial Intelligence in Games
  • Reinforcement Learning in Robotics
  • Multimodal Machine Learning Applications
  • Machine Learning and ELM
  • Advanced Neural Network Applications
  • Digital Games and Media

Best Publications

  • ICDAR 2015 competition on Robust Reading

    Dimosthenis Karatzas;Lluis Gomez-Bigorda;Anguelos Nicolaou;Suman Ghosh

  • Class-incremental learning: survey and performance evaluation on image classification

    Marc Masana;Xialei Liu;Bartlomiej Twardowski;Mikel Menta

  • RankIQA: Learning from Rankings for No-Reference Image Quality Assessment

    Xialei Liu;Joost van de Weijer;Andrew D. Bagdanov

  • Boosting color saliency in image feature detection

    J. van de Weijer;T. Gevers;A.D. Bagdanov

  • Person Re-Identification by Iterative Re-Weighted Sparse Ranking

    Giuseppe Lisanti;Iacopo Masi;Andrew D. Bagdanov;Alberto Del Bimbo

  • Color attributes for object detection

    Fahad Shahbaz Khan;Rao Muhammad Anwer;Joost van de Weijer;Andrew D. Bagdanov

  • Leveraging Unlabeled Data for Crowd Counting by Learning to Rank

    Xialei Liu;Joost van de Weijer;Andrew D. Bagdanov

  • Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting

    Xialei Liu;Marc Masana;Luis Herranz;Joost Van de Weijer

  • Harmony Potentials

    Xavier Boix;Josep M. Gonfaus;Joost Weijer;Andrew D. Bagdanov

  • Harmony potentials for joint classification and segmentation

    Josep M. Gonfaus;Xavier Boix;Joost van de Weijer;Andrew D. Bagdanov

  • Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank

    Xialei Liu;Joost van de Weijer;Andrew D. Bagdanov

  • The florence 2D/3D hybrid face dataset

    Andrew D. Bagdanov;Alberto Del Bimbo;Iacopo Masi

  • Coloring Action Recognition in Still Images

    Fahad Shahbaz Khan;Rao Muhammad Anwer;Joost Weijer;Andrew D. Bagdanov

  • Trademark matching and retrieval in sports video databases

    Andrew D. Bagdanov;Lamberto Ballan;Marco Bertini;Alberto Del Bimbo

  • Generative Feature Replay For Class-Incremental Learning

    Xialei Liu;Chenshen Wu;Mikel Menta;Luis Herranz

  • Semantic annotation and retrieval of video events using multimedia ontologies

    A.D. Bagdanov;M. Bertini;A. Del Bimbo;G. Serra

  • Accurate Moving Cast Shadow Suppression Based on Local Color Constancy Detection

    A. Amato;M. G. Mozerov;A. D. Bagdanov;J. Gonzalez

  • Sparse radial sampling LBP for writer identification

    Anguelos Nicolaou;Andrew D. Bagdanov;Marcus Liwicki;Dimosthenis Karatzas

  • Color Feature Detection

    Theo Gevers;Joost van de Weijer;Harro Stokman

  • Portmanteau Vocabularies for Multi-Cue Image Representation

    Fahad S. Khan;Joost Weijer;Andrew D. Bagdanov;Maria Vanrell

  • First Order Gaussian Graphs for Efficient Structure Classification

    Andrew D. Bagdanov;Marcel Worring

  • Projection profile based skew estimation algorithm for JBIG compressed images

    A. Bagdanov;J. Kanai

  • Class-incremental learning: survey and performance evaluation

    Marc Masana;Xialei Liu;Bartlomiej Twardowski;Mikel Menta

Frequent Co-Authors

Alberto Del Bimbo
Alberto Del Bimbo University of Florence
Joost van de Weijer
Joost van de Weijer Autonomous University of Barcelona
Marco Bertini
Marco Bertini University of Florence
Dimosthenis Karatzas
Dimosthenis Karatzas Autonomous University of Barcelona
Marcel Worring
Marcel Worring University of Amsterdam
Fahad Shahbaz Khan
Fahad Shahbaz Khan Mohamed bin Zayed University of Artificial Intelligence
Michael Felsberg
Michael Felsberg Linköping University
Joan Serrat
Joan Serrat Universitat Politècnica de Catalunya
Antonio M. López
Antonio M. López Autonomous University of Barcelona
Arnold W. M. Smeulders
Arnold W. M. Smeulders University of Amsterdam

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