H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 43 Citations 7,827 181 World Ranking 3959 National Ranking 12

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Machine learning, Feature extraction and Classifier. His work in Deep learning, Feature, Contextual image classification, Pattern recognition and Support vector machine are all subfields of Artificial intelligence research. His work in the fields of Pattern recognition, such as Segmentation and Feature matching, overlaps with other areas such as Signature and Polygon.

His Artificial neural network, Genetic algorithm and Feature selection study are his primary interests in Machine learning. His Feature extraction study which covers Field that intersects with Iris recognition and Feature learning. Luiz S. Oliveira combines subjects such as Data mining and Feature set with his study of Classifier.

His most cited work include:

  • A Dataset for Breast Cancer Histopathological Image Classification (379 citations)
  • Breast cancer histopathological image classification using Convolutional Neural Networks (332 citations)
  • Automatic recognition of handwritten numerical strings: a recognition and verification strategy (205 citations)

What are the main themes of his work throughout his whole career to date?

Luiz S. Oliveira mostly deals with Artificial intelligence, Pattern recognition, Machine learning, Classifier and Feature extraction. His Support vector machine, Segmentation, Convolutional neural network, Artificial neural network and Feature vector investigations are all subjects of Artificial intelligence research. His Pattern recognition study incorporates themes from Local binary patterns, Image and Feature.

His Machine learning course of study focuses on Pattern recognition and Identification. The concepts of his Classifier study are interwoven with issues in Pattern recognition problem and Biometrics. His work in Feature extraction addresses subjects such as Contextual image classification, which are connected to disciplines such as Transfer of learning.

He most often published in these fields:

  • Artificial intelligence (82.65%)
  • Pattern recognition (52.51%)
  • Machine learning (32.42%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (82.65%)
  • Pattern recognition (52.51%)
  • Machine learning (32.42%)

In recent papers he was focusing on the following fields of study:

Luiz S. Oliveira mainly focuses on Artificial intelligence, Pattern recognition, Machine learning, Deep learning and Classifier. His study in Feature extraction, Image, Segmentation, Representation and Convolutional neural network are all subfields of Artificial intelligence. His Convolutional neural network research is multidisciplinary, incorporating perspectives in Object detection, Task, Feature learning and Robustness.

His work deals with themes such as Contextual image classification, Identification, Local binary patterns and Transfer of learning, which intersect with Pattern recognition. His study looks at the relationship between Machine learning and fields such as Adversarial system, as well as how they intersect with chemical problems. His Classifier research is multidisciplinary, incorporating elements of Biometrics, Data stream mining, Resampling, Evolutionary algorithm and Discriminative model.

Between 2018 and 2021, his most popular works were:

  • Multiple instance learning for histopathological breast cancer image classification (102 citations)
  • Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses (82 citations)
  • Double Transfer Learning for Breast Cancer Histopathologic Image Classification (15 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Artificial intelligence, Pattern recognition, Machine learning, Classifier and Feature extraction are his primary areas of study. His study in Deep learning, Adversarial system, Robustness, Image processing and Biometrics is carried out as part of his studies in Artificial intelligence. His Pattern recognition research is multidisciplinary, relying on both Contextual image classification and Image.

The various areas that he examines in his Machine learning study include Representation and Field. His Classifier research integrates issues from Resampling, Random forest, Discriminative model and Imbalanced data. He has researched Feature extraction in several fields, including Learning classifier system, Cognitive neuroscience of visual object recognition and Training set.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

A Dataset for Breast Cancer Histopathological Image Classification

Fabio A. Spanhol;Luiz S. Oliveira;Caroline Petitjean;Laurent Heutte.
IEEE Transactions on Biomedical Engineering (2016)

523 Citations

Breast cancer histopathological image classification using Convolutional Neural Networks

Fabio Alexandre Spanhol;Luiz S. Oliveira;Caroline Petitjean;Laurent Heutte.
international joint conference on neural network (2016)

484 Citations

Automatic recognition of handwritten numerical strings: a recognition and verification strategy

L.S. Oliveira;R. Sabourin;F. Bortolozzi;C.Y. Suen.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2002)

309 Citations

Dynamic selection of classifiers-A comprehensive review

Alceu S. Britto;Alceu S. Britto;Robert Sabourin;Luiz E. S. Oliveira.
Pattern Recognition (2014)

259 Citations

Reducing forgeries in writer-independent off-line signature verification through ensemble of classifiers

D. Bertolini;L. S. Oliveira;E. Justino;R. Sabourin.
Pattern Recognition (2010)

230 Citations

A METHODOLOGY FOR FEATURE SELECTION USING MULTIOBJECTIVE GENETIC ALGORITHMS FOR HANDWRITTEN DIGIT STRING RECOGNITION

Luiz E. Soares de Oliveira;Robert Sabourin;Flávio Bortolozzi;Ching Y. Suen.
International Journal of Pattern Recognition and Artificial Intelligence (2003)

204 Citations

PKLot – A robust dataset for parking lot classification

Paulo R.L. de Almeida;Luiz S. Oliveira;Alceu S. Britto;Eunelson J. Silva.
Expert Systems With Applications (2015)

180 Citations

Texture-based descriptors for writer identification and verification

D. Bertolini;L.S. Oliveira;E. Justino;R. Sabourin.
Expert Systems With Applications (2013)

174 Citations

Learning features for offline handwritten signature verification using deep convolutional neural networks

Luiz G. Hafemann;Robert Sabourin;Luiz S. Oliveira.
Pattern Recognition (2017)

170 Citations

A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector

Rayson Laroca;Evair Severo;Luiz A. Zanlorensi;Luiz S. Oliveira.
international joint conference on neural network (2018)

159 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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