H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 53 Citations 11,070 147 World Ranking 2441 National Ranking 1304

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Artificial intelligence, Pattern recognition, Machine learning, Facial expression and Mathematical optimization are his primary areas of study. His Artificial intelligence research focuses on subjects like Computer vision, which are linked to Activity recognition. His Pattern recognition study combines topics in areas such as Contextual image classification and Feature.

The study incorporates disciplines such as Facial recognition system and Outlier in addition to Machine learning. His Facial expression research is multidisciplinary, incorporating elements of Margin, Speech recognition and Neuroscience. Fernando De la Torre combines subjects such as Algorithm, Stochastic gradient descent and Backpropagation with his study of Mathematical optimization.

His most cited work include:

  • Supervised Descent Method and Its Applications to Face Alignment (1614 citations)
  • A Framework for Robust Subspace Learning (546 citations)
  • Facing Imbalanced Data--Recommendations for the Use of Performance Metrics (276 citations)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Facial expression. Support vector machine, Discriminative model, Robustness, Facial recognition system and Feature extraction are among the areas of Artificial intelligence where the researcher is concentrating his efforts. Fernando De la Torre interconnects Pose and Outlier in the investigation of issues within Discriminative model.

His Pattern recognition research focuses on Cluster analysis and how it relates to Synthetic data. His research in Machine learning intersects with topics in Classifier and Kernel. As a member of one scientific family, he mostly works in the field of Facial expression, focusing on Speech recognition and, on occasion, Facial Action Coding System.

He most often published in these fields:

  • Artificial intelligence (80.75%)
  • Pattern recognition (39.57%)
  • Computer vision (28.88%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (80.75%)
  • Computer vision (28.88%)
  • Deep learning (4.81%)

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

Fernando De la Torre focuses on Artificial intelligence, Computer vision, Deep learning, Robustness and Human–computer interaction. Fernando De la Torre has researched Artificial intelligence in several fields, including Scalability and Pattern recognition. His work carried out in the field of Pattern recognition brings together such families of science as Artificial neural network and Multilayer perceptron.

His Monocular, Pose and Rendering study, which is part of a larger body of work in Computer vision, is frequently linked to Unit and Generative model, bridging the gap between disciplines. His studies deal with areas such as Cross-validation and Word error rate as well as Robustness. In his research, Functional data analysis, Linear regression and Least squares is intimately related to Face, which falls under the overarching field of Human–computer interaction.

Between 2017 and 2021, his most popular works were:

  • A Functional Regression Approach to Facial Landmark Tracking (25 citations)
  • Increasing Robustness in the Detection of Freezing of Gait in Parkinson’s Disease (20 citations)
  • Inverse Composition Discriminative Optimization for Point Cloud Registration (15 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

His main research concerns Artificial intelligence, Pattern recognition, Convolutional neural network, Deep learning and Codec. Many of his studies on Artificial intelligence apply to Computer vision as well. His work on Segmentation and Image segmentation as part of general Pattern recognition study is frequently linked to Weighting, bridging the gap between disciplines.

His research integrates issues of Network architecture, Visualization and Hybrid system in his study of Convolutional neural network. His Deep learning research includes themes of Speech processing, Word error rate, Artificial neural network, Multilayer perceptron and Mel-frequency cepstrum. As part of the same scientific family, Fernando De la Torre usually focuses on Motion, concentrating on Face and intersecting with Functional data analysis and Least squares.

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

Supervised Descent Method and Its Applications to Face Alignment

Xuehan Xiong;Fernando De la Torre.
computer vision and pattern recognition (2013)

2220 Citations

A Framework for Robust Subspace Learning

Fernando De La Torre;Michael J. Black.
International Journal of Computer Vision (2003)

665 Citations

Max-margin early event detectors

Minh Hoai;Fernando Torre.
computer vision and pattern recognition (2012)

386 Citations

Detecting depression from facial actions and vocal prosody

Jeffrey F. Cohn;Tomas Simon Kruez;Iain Matthews;Ying Yang.
affective computing and intelligent interaction (2009)

378 Citations

Facial Expression Analysis.

Fernando De la Torre;Jeffrey F. Cohn.
Visual Analysis of Humans (2011)

373 Citations

Facing Imbalanced Data--Recommendations for the Use of Performance Metrics

Laszlo A. Jeni;Jeffrey F. Cohn;Fernando De La Torre.
affective computing and intelligent interaction (2013)

355 Citations

Joint segmentation and classification of human actions in video

Minh Hoai;Zhen-Zhong Lan;Fernando De la Torre.
computer vision and pattern recognition (2011)

326 Citations

Factorized graph matching

Feng Zhou;Fernando De la Torre.
computer vision and pattern recognition (2012)

313 Citations

Selective Transfer Machine for Personalized Facial Action Unit Detection

Wen-Sheng Chu;Fernando De La Torre;Jeffery F. Cohn.
computer vision and pattern recognition (2013)

280 Citations

Optimal feature selection for support vector machines

Minh Hoai Nguyen;Fernando de la Torre.
Pattern Recognition (2010)

271 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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