H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 39 Citations 5,774 224 World Ranking 4658 National Ranking 123

Research.com Recognitions

Awards & Achievements

2002 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to pattern recognition, image processing and machine learning.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Terry Caelli focuses on Artificial intelligence, Pattern recognition, Computer vision, Remote sensing and Image processing. His study in Artificial intelligence focuses on Texture, Orientation, Feature, Pixel and Scale space. Terry Caelli combines subjects such as Texture and Markov model with his study of Pattern recognition.

Terry Caelli studied Computer vision and Extended Kalman filter that intersect with Bayesian probability, Tracking system, Bayesian filtering and Tracking. The concepts of his Remote sensing study are interwoven with issues in Tropical and subtropical dry broadleaf forests, Dry season and Canopy. His Image processing research is multidisciplinary, incorporating elements of Differential geometry, Specular highlight, Computer graphics and Regular polygon.

His most cited work include:

  • On perceptual analyzers underlying visual texture discrimination: Part II (194 citations)
  • An eigenspace projection clustering method for inexact graph matching (182 citations)
  • On the classification of image regions by colour, texture and shape (138 citations)

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

Terry Caelli spends much of his time researching Artificial intelligence, Pattern recognition, Computer vision, Pattern recognition and Image processing. The study of Artificial intelligence is intertwined with the study of Machine learning in a number of ways. Many of his studies on Machine learning apply to Hidden Markov model as well.

Terry Caelli has included themes like Feature, Edge detection, Feature and Communication in his Pattern recognition study. His Computer vision study typically links adjacent topics like Perception. Cognitive neuroscience of visual object recognition is a subfield of Object that Terry Caelli explores.

He most often published in these fields:

  • Artificial intelligence (64.79%)
  • Pattern recognition (29.88%)
  • Computer vision (28.99%)

What were the highlights of his more recent work (between 2006-2021)?

  • Artificial intelligence (64.79%)
  • Computer vision (28.99%)
  • Pattern recognition (29.88%)

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

Terry Caelli mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Theoretical computer science and Data mining. His research in Artificial intelligence intersects with topics in Machine learning, Encoder and Probability density function. He focuses mostly in the field of Computer vision, narrowing it down to matters related to Kalman filter and, in some cases, Motion capture and Rehabilitation exercise.

His Pattern recognition study integrates concerns from other disciplines, such as Object detection, Histogram, Fiducial points, Environmental monitoring and Data science. His Theoretical computer science research is multidisciplinary, incorporating perspectives in Tree, Development and Computational complexity theory. His Data mining study incorporates themes from Genetic algorithm, Mutual information, Interpretation and User interface.

Between 2006 and 2021, his most popular works were:

  • Ecological fingerprinting of ecosystem succession: Estimating secondary tropical dry forest structure and diversity using imaging spectroscopy (110 citations)
  • Real-Time Discriminative Background Subtraction (89 citations)
  • Hyperspectral discrimination of tropical dry forest lianas and trees: Comparative data reduction approaches at the leaf and canopy levels (86 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

His primary scientific interests are in Artificial intelligence, Computer vision, Remote sensing, Spectral signature and Hyperspectral imaging. His Artificial intelligence research incorporates themes from Algorithm, Markov model and Pattern recognition. His study in Computer vision is interdisciplinary in nature, drawing from both Rehabilitation and Rehabilitation exercise.

His Remote sensing research incorporates elements of Telecommunications and Doppler radar. His work carried out in the field of Spectral signature brings together such families of science as Feature selection, Principal component analysis, Satellite imagery and Feature vector. His Hyperspectral imaging research is multidisciplinary, relying on both Image sensor, Image processing, Canopy, Feature extraction and Liana.

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.

Best Publications

An eigenspace projection clustering method for inexact graph matching

T. Caelli;S. Kosinov.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

278 Citations

On perceptual analyzers underlying visual texture discrimination: Part II

Terry Caelli;Bela Julesz;Edgar Gilbert.
Biological Cybernetics (1978)

243 Citations

On the classification of image regions by colour, texture and shape

Terry M. Caelli;David Reye.
Pattern Recognition (1993)

225 Citations

Computation of surface geometry and segmentation using covariance techniques

J. Berkmann;T. Caelli.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1994)

172 Citations

Visual Perception Theory and Practice

Terry Caelli.
(1981)

167 Citations

Graphical Models and Point Pattern Matching

T.S. Caetano;T. Caelli;D. Schuurmans;D.A.C. Barone.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

167 Citations

Ecological fingerprinting of ecosystem succession: Estimating secondary tropical dry forest structure and diversity using imaging spectroscopy

M. Kalacska;G.A. Sanchez-Azofeifa;B. Rivard;T. Caelli.
Remote Sensing of Environment (2007)

161 Citations

Three Processing Characteristics of Visual Texture Segmentation

Terry Caelli.
Spatial Vision (1985)

158 Citations

Hidden Markov models: applications in computer vision

Horst O. Bunke;Terry Caelli.
(2001)

137 Citations

Subjective Lorentz transformations and the perception of motion

Terry Caelli;William Hoffman;Harold Lindman.
Journal of the Optical Society of America (1978)

129 Citations

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