H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 92 Citations 41,959 341 World Ranking 229 National Ranking 3

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Algorithm. His study in Artificial intelligence focuses on Convolutional neural network, Robustness, Artificial neural network, Segmentation and Training set. Ian Reid interconnects Video tracking, Structured prediction, Zero shot learning, Benchmark and Generative grammar in the investigation of issues within Pattern recognition.

When carried out as part of a general Machine learning research project, his work on Deep learning and Feature is frequently linked to work in Context model and Social robot, therefore connecting diverse disciplines of study. His work is dedicated to discovering how Algorithm, Cut are connected with Graph theory and Discrete optimization and other disciplines. The study incorporates disciplines such as Humanoid robot, Single camera, Visual odometry and Virtual reality in addition to Monocular.

His most cited work include:

  • MonoSLAM: Real-Time Single Camera SLAM (2654 citations)
  • Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (1201 citations)
  • RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation (1131 citations)

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

Ian Reid spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Segmentation. His is doing research in Deep learning, Object, Convolutional neural network, Tracking and Artificial neural network, both of which are found in Artificial intelligence. His biological study deals with issues like Benchmark, which deal with fields such as Video tracking.

He combines subjects such as Simultaneous localization and mapping and Affine transformation with his study of Computer vision. His Pattern recognition study incorporates themes from Contextual image classification, Image and Probabilistic logic. His biological study spans a wide range of topics, including Pixel and Pascal.

He most often published in these fields:

  • Artificial intelligence (85.09%)
  • Computer vision (47.15%)
  • Pattern recognition (20.61%)

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

  • Artificial intelligence (85.09%)
  • Computer vision (47.15%)
  • Machine learning (16.45%)

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

Ian Reid mainly investigates Artificial intelligence, Computer vision, Machine learning, Pattern recognition and Deep learning. Segmentation, Object, Benchmark, Artificial neural network and Convolutional neural network are the core of his Artificial intelligence study. Many of his research projects under Computer vision are closely connected to Block with Block, tying the diverse disciplines of science together.

As part of one scientific family, Ian Reid deals mainly with the area of Machine learning, narrowing it down to issues related to the Hidden Markov model, and often Inference. His research in Pattern recognition intersects with topics in Margin, Image, Image retrieval and Autoencoder. His work deals with themes such as Ground truth, Noise, Feature learning and Set, which intersect with Deep learning.

Between 2018 and 2021, his most popular works were:

  • Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression (320 citations)
  • Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks (112 citations)
  • Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video (89 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary areas of study are Artificial intelligence, Machine learning, Deep learning, Computer vision and Segmentation. Artificial intelligence connects with themes related to Pattern recognition in his study. His work investigates the relationship between Machine learning and topics such as Sample that intersect with problems in Visualization.

Ian Reid works mostly in the field of Deep learning, limiting it down to topics relating to Feature learning and, in certain cases, Upper and lower bounds, Centroid, Training set, Linearization and Function. The Iterative reconstruction, Monocular and High-dynamic-range imaging research Ian Reid does as part of his general Computer vision study is frequently linked to other disciplines of science, such as Visibility, therefore creating a link between diverse domains of science. His research integrates issues of Bundle, Feature, Trajectory and Bundle adjustment in his study of Simultaneous localization and mapping.

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

MonoSLAM: Real-Time Single Camera SLAM

A.J. Davison;I.D. Reid;N.D. Molton;O. Stasse.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

3795 Citations

Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age

Cesar Cadena;Luca Carlone;Henry Carrillo;Yasir Latif.
IEEE Transactions on Robotics (2016)

1349 Citations

Articulated body motion capture by annealed particle filtering

J. Deutscher;A. Blake;I. Reid.
computer vision and pattern recognition (2000)

1256 Citations

RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation

Guosheng Lin;Anton Milan;Chunhua Shen;Ian Reid.
computer vision and pattern recognition (2017)

1184 Citations

Single View Metrology

A. Criminisi;I. Reid;A. Zisserman.
International Journal of Computer Vision (2000)

998 Citations

Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

Fayao Liu;Chunhua Shen;Guosheng Lin;Ian Reid.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2016)

696 Citations

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

Ravi Garg;B. G. Vijay Kumar;Gustavo Carneiro;Ian D. Reid.
european conference on computer vision (2016)

688 Citations

Stable multi-target tracking in real-time surveillance video

Ben Benfold;Ian Reid.
computer vision and pattern recognition (2011)

669 Citations

MOT16: A Benchmark for Multi-Object Tracking

Anton Milan;Laura Leal-Taixé;Ian D. Reid;Stefan Roth.
arXiv: Computer Vision and Pattern Recognition (2016)

652 Citations

Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

Guosheng Lin;Chunhua Shen;Anton van den Hengel;Ian Reid.
computer vision and pattern recognition (2016)

635 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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