World's Best Scientists 2026 revealed!
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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
64
Citations
18577
World Ranking
2573
National Ranking
147

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Gustavo Carneiro is affiliated with the University of Adelaide in Australia and has a significant body of work spanning computer science and medicine. Their research primarily focuses on artificial intelligence and its applications in medical imaging and cancer detection, with an emphasis on machine learning and data classification methodologies.

The scientist has contributed to 261 publications in computer science and 191 publications in medicine. Within these fields, the most prominent subfields of study include:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Oncology
  • Civil and Structural Engineering

Gustavo Carneiro's main research topics encompass:

  • Machine Learning and Data Classification
  • COVID-19 diagnosis using AI
  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Anomaly Detection Techniques and Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications

The scientist frequently publishes in venues such as:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Pattern Recognition
  • Medical Image Analysis
  • IEEE Transactions on Medical Imaging

Among recent papers authored or co-authored by Gustavo Carneiro are:

  • "Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning," 2021, presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation," 2022, presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis," 2021, published in BMC Cancer
  • "ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification," 2022, presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Deep One-Class Classification via Interpolated Gaussian Descriptor," 2022, presented at the Proceedings of the AAAI Conference on Artificial Intelligence

Gustavo Carneiro frequently collaborates with a consistent group of co-authors, including:

  • Yuyuan Liu
  • Fengbei Liu
  • Chong Wang
  • Vasileios Belagiannis
  • Thanh-Toan Do

Best Publications

  • Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

    Ravi Garg;B. G. Vijay Kumar;Gustavo Carneiro;Ian D. Reid

  • Supervised Learning of Semantic Classes for Image Annotation and Retrieval

    G. Carneiro;A.B. Chan;P.J. Moreno;N. Vasconcelos

  • Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

    M. Jorge Cardoso;Tal Arbel;Gustavo Carneiro;Tanveer Syeda-Mahmood

  • Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

    Ravi Garg;Vijay Kumar Bg;Gustavo Carneiro;Ian Reid

  • Weakly-Supervised Video Anomaly Detection With Robust Temporal Feature Magnitude Learning

    Yu Tian;Guansong Pang;Yuanhong Chen;Rajvinder Singh

  • Multi-modal Cycle-Consistent Generalized Zero-Shot Learning

    Rafael Felix;B. G. Vijay Kumar;Ian D. Reid;Gustavo Carneiro

  • Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.

    Tuan Anh Ngo;Zhi Lu;Gustavo Carneiro

  • A deep learning approach for the analysis of masses in mammograms with minimal user intervention.

    Neeraj Dhungel;Gustavo Carneiro;Andrew P. Bradley

  • Smart Mining for Deep Metric Learning

    Ben Harwood;Vijay Kumar B. G;Gustavo Carneiro;Ian Reid

  • Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

    Unknown

  • Learning Local Image Descriptors with Deep Siamese and Triplet Convolutional Networks by Minimizing Global Loss Functions

    Vijay Kumar B G;Gustavo Carneiro;Ian Reid

  • Hidden stratification causes clinically meaningful failures in machine learning for medical imaging

    Luke Oakden-Rayner;Jared Dunnmon;Gustavo Carneiro;Christopher Re

  • Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models

    Gustavo Carneiro;Jacinto C. Nascimento;Andrew P. Bradley

  • An Improved Joint Optimization of Multiple Level Set Functions for the Segmentation of Overlapping Cervical Cells

    Zhi Lu;Gustavo Carneiro;Andrew P. Bradley

  • Detection and Measurement of Fetal Anatomies from Ultrasound Images using a Constrained Probabilistic Boosting Tree

    G. Carneiro;B. Georgescu;S. Good;D. Comaniciu

  • Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests

    Neeraj Dhungel;Gustavo Carneiro;Andrew P. Bradley

  • Cross-layer design in 4G wireless terminals

    G. Carneiro;J. Ruela;M. Ricardo

  • Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support : 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

    Danail Stoyanov;Zeike Taylor;Gustavo Carneiro;Tanveer Syeda-Mahmood

  • The Segmentation of the Left Ventricle of the Heart From Ultrasound Data Using Deep Learning Architectures and Derivative-Based Search Methods

    G. Carneiro;J. C. Nascimento;A. Freitas

  • Formulating semantic image annotation as a supervised learning problem

    G. Carneiro;N. Vasconcelos

  • Self-Supervised Monocular Trained Depth Estimation Using Self-Attention and Discrete Disparity Volume

    Adrian Johnston;Gustavo Carneiro

  • Deep Learning and Convolutional Neural Networks for Medical Image Computing

    Le Lu;Yefeng Zheng;Gustavo Carneiro;Lin Yang

  • Deep Learning and Data Labeling for Medical Applications

    Gustavo Carneiro;Diana Mateus;Loïc Peter;Andrew Bradley

  • Learning Local Image Descriptors with Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions

    Vijay Kumar B G;Gustavo Carneiro;Ian Reid

Frequent Co-Authors

Andrew P. Bradley
Andrew P. Bradley Queensland University of Technology
Ian Reid
Ian Reid University of Adelaide
Dorin Comaniciu
Dorin Comaniciu Siemens (United States)
Nuno Vasconcelos
Nuno Vasconcelos University of California, San Diego
João Paulo Papa
João Paulo Papa Sao Paulo State University
Allan D. Jepson
Allan D. Jepson University of Toronto
João Manuel R. S. Tavares
João Manuel R. S. Tavares University of Porto
Nassir Navab
Nassir Navab Technical University of Munich
Bogdan Georgescu
Bogdan Georgescu Princeton University
Tat-Jun Chin
Tat-Jun Chin University of Adelaide

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