Ben Upcroft

10.2k citations
114 papers · 6.3k indexed · 4 hit papers · h-index 26

Ben Upcroft

113 papers receiving 6.1k citations

Hit Papers

The limits and potentials of deep learning for robotics309201520262018202250010001.5k2.0k

Peers

Ben Upcroft
Comparison fields: 5 of 154
  • Computer Vision and Pattern Recognition 3.4k
  • Aerospace Engineering 1.8k
  • Analytical Chemistry 381
  • Plant Science 1.3k
  • Geology 191
Replace Juan Nieto with:
Juan Nieto Switzerland
Salah Sukkarieh Australia
Mingxing Tan United States
Simon X. Yang Canada
Peihua Li China
Qibin Hou China
Tom Duckett United Kingdom
Edward Jones Ireland
Ruoming Pang United States
Feras Dayoub Australia
Ben Upcroft relative to Juan Nieto Switzerland Juan Nieto's profile →
Citations per field
00.5×3.2×
Juan Nieto · 1×
Citations per year

Countries citing papers authored by Ben Upcroft

Since Specialization
Citations

This map shows the geographic impact of Ben Upcroft's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ben Upcroft with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Upcroft more than expected).

Fields of papers citing papers by Ben Upcroft

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ben Upcroft. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ben Upcroft. The network helps show where Ben Upcroft may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Ben Upcroft, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ben Upcroft Line = papers co-authored together Ben Upcroft links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
The limits and potentials of deep learning for roboticsbreakdown →
2018309
2
Simple online and realtime trackingbreakdown →
20162225
3
Transferring Vision-based Robotic Reaching Skills from Simulation to Real World
20161
4
A robustness analysis of Deep Q Networks
20161
5
Multimodal deep autoencoders for control of a mobile robot
201514
6
Continuous factor graphs for holistic scene understanding
20152
7
Repeatable condition-invariant visual odometry for sequence-based place recognition
20151
8
Constructing abstract maps from spatial descriptions for goal-directed exploration
20151
9
Towards vision-based deep reinforcement learning for robotic motion control
20159
10
Fine-grained plant classification using convolutional neural networks for feature extraction
201423
11 201312
12
One Robot, Eight Hours, and Twenty Four Thousand People
20131
13
Visual sea-floor mapping from low overlap imagery using bi-objective bundle adjustment and constrained motion
20126
14
Feature-based visual odometry and featureless place recognition for SLAM in 2.5D environments
20113
15
Towards Automatic Object Segmentation with Sequential Multiple Views
20114
16
Unaided stereo vision based pose estimation
201025
17
Graphcut-based interactive segmentation using colour and depth cues
20107
18
Bayesian filtering over compressed appearance states
20071
19
Fast re-parameterisation of Gaussian mixture models for robotics applications
20049
20
Dynamical Tunneling of Ultracold Atoms
20018

About Ben Upcroft

Ben Upcroft is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Geology, Artificial Intelligence and Media Technology, having authored 114 papers that have together received 6.3k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (47 papers), Target Tracking and Data Fusion in Sensor Networks (22 papers), Advanced Image and Video Retrieval Techniques (22 papers), Advanced Vision and Imaging (17 papers), Smart Agriculture and AI (13 papers), Robotic Path Planning Algorithms (11 papers), Video Surveillance and Tracking Methods (8 papers) and 3D Surveying and Cultural Heritage (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.4k citations), Aerospace Engineering (1.8k citations), Analytical Chemistry (381 citations), Plant Science (1.3k citations) and Geology (191 citations). Ben Upcroft has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Zongyuan Ge, Alex Bewley, Fábio Ramos, Lionel Ott, Feras Dayoub, Chris McCool, Tristán Pérez, Michael Milford, Inkyu Sa and Niko Sünderhauf. Their work appears in journals such as Journal of Field Robotics, Nature, Physical Review A, IEEE Transactions on Robotics and IEEE Robotics and Automation Letters.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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