D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 42 Citations 12,091 256 World Ranking 5146 National Ranking 320

Research.com Recognitions

Awards & Achievements

2016 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to computer vision and applications

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary scientific interests are in Artificial intelligence, Computer vision, Image processing, Pattern recognition and Image segmentation. His Segmentation, Feature extraction, Outlier, Motion estimation and Motion analysis investigations are all subjects of Artificial intelligence research. The study of Computer vision is intertwined with the study of Pattern recognition in a number of ways.

His Image processing study also includes fields such as

  • Sketch that connect with fields like Test data, Teleconference and Digital television,
  • Multimedia which is related to area like The Internet, Presentation and Immersion. His Pattern recognition study incorporates themes from Contextual image classification and Robustness. His research in Image segmentation intersects with topics in Feature, Inpainting, Medical imaging and Optic disc.

His most cited work include:

  • Introductory Techniques for 3-D Computer Vision (1444 citations)
  • A compact algorithm for rectification of stereo pairs (596 citations)
  • Efficient stereo with multiple windowing (254 citations)

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

Emanuele Trucco spends much of his time researching Artificial intelligence, Computer vision, Retinal, Pattern recognition and Retina. His Artificial intelligence research focuses on Segmentation, Image segmentation, Feature extraction, Contextual image classification and Feature. His Computer vision study frequently draws connections between related disciplines such as Optic disc.

The concepts of his Retinal study are interwoven with issues in Diabetic retinopathy, Internal medicine and Cardiology. Emanuele Trucco specializes in Pattern recognition, namely Support vector machine. His research investigates the link between Tracking and topics such as Particle swarm optimization that cross with problems in Pose.

He most often published in these fields:

  • Artificial intelligence (62.25%)
  • Computer vision (50.66%)
  • Retinal (20.86%)

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

  • Retinal (20.86%)
  • Internal medicine (8.61%)
  • Cardiology (6.62%)

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

Emanuele Trucco mostly deals with Retinal, Internal medicine, Cardiology, Retina and Ophthalmology. Emanuele Trucco combines subjects such as Perivascular space, Blood pressure and Vein with his study of Retinal. His Retina research also works with subjects such as

  • Fundus camera that connect with fields like Retinal blood vessels, Pattern recognition and Birth cohort,
  • Cohort that connect with fields like Older population, Small vessel, Multivariate statistics and Cognition.

His work carried out in the field of Fundus brings together such families of science as Optic disc, Computer vision and Artificial intelligence. The Feature extraction and Image segmentation research Emanuele Trucco does as part of his general Computer vision study is frequently linked to other disciplines of science, such as Fractal dimension, therefore creating a link between diverse domains of science. His Artificial intelligence research includes elements of Neuroimaging and Disease, Cognitive impairment.

Between 2017 and 2021, his most popular works were:

  • Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: A systematic review (72 citations)
  • Towards Standardization of Quantitative Retinal Vascular Parameters: Comparison of SIVA and VAMPIRE Measurements in the Lothian Birth Cohort 1936 (25 citations)
  • Retinal microvasculature and cerebral small vessel disease in the Lothian Birth Cohort 1936 and Mild Stroke Study (23 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

His main research concerns Retinal, Retina, Internal medicine, Artificial intelligence and Dementia. His Retina research is multidisciplinary, relying on both Ophthalmology and Fundus camera, Fundus. The various areas that Emanuele Trucco examines in his Internal medicine study include Type 2 diabetes and Cardiology.

His Artificial intelligence research includes themes of Retinal Vein and Pattern recognition. His Feature extraction study introduces a deeper knowledge of Computer vision. The study incorporates disciplines such as Cluster analysis and Data set in addition to Computer vision.

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

Introductory Techniques for 3-D Computer Vision

Emanuele Trucco;Alessandro Verri.
(1998)

3674 Citations

A compact algorithm for rectification of stereo pairs

Andrea Fusiello;Emanuele Trucco;Alessandro Verri.
machine vision applications (2000)

1226 Citations

Efficient stereo with multiple windowing

A. Fusiello;V. Roberto;E. Trucco.
computer vision and pattern recognition (1997)

463 Citations

FABC: Retinal Vessel Segmentation Using AdaBoost

C A Lupascu;D Tegolo;E Trucco.
international conference of the ieee engineering in medicine and biology society (2010)

407 Citations

Making good features track better

T. Tommasini;A. Fusiello;E. Trucco;V. Roberto.
computer vision and pattern recognition (1998)

268 Citations

Video Tracking: A Concise Survey

E. Trucco;K. Plakas.
IEEE Journal of Oceanic Engineering (2006)

232 Citations

Dictionary of Computer Vision and Image Processing

Robert B. Fisher;Toby P. Breckon;Kenneth Dawson-Howe;Andrew Fitzgibbon.
(2005)

190 Citations

Experiments in curvature-based segmentation of range data

E. Trucco;R.B. Fisher.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1995)

177 Citations

Validating retinal fundus image analysis algorithms: issues and a proposal.

Emanuele Trucco;Alfredo Ruggeri;Thomas Karnowski;Luca Giancardo.
Investigative Ophthalmology & Visual Science (2013)

176 Citations

Robust motion and correspondence of noisy 3-D point sets with missing data

Emanuele Trucco;Andrea Fusiello;Vito Roberto.
Pattern Recognition Letters (1999)

176 Citations

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