Daniel Lenton

Daniel Lenton

Imperial College London

H-index: 4

Europe-United Kingdom

About Daniel Lenton

Daniel Lenton, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at Imperial College London, specializes in the field of Computer Vision, Deep Learning, Reinforcement Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Accelerating Deep Learning using Ivy

Image processing system and method

Unsupervised path regression networks

Waypoint planning networks

End-to-end egospheric spatial memory

Ivy: Templated deep learning for inter-framework portability

Learning To Find Shortest Collision-Free Paths From Images.

Morefusion: Multi-object reasoning for 6d pose estimation from volumetric fusion

Daniel Lenton Information

University

Position

PhD Student Dyson Robotics Lab

Citations(all)

118

Citations(since 2020)

118

Cited By

13

hIndex(all)

4

hIndex(since 2020)

4

i10Index(all)

2

i10Index(since 2020)

2

Email

University Profile Page

Google Scholar

Daniel Lenton Skills & Research Interests

Computer Vision

Deep Learning

Reinforcement Learning

Top articles of Daniel Lenton

Accelerating Deep Learning using Ivy

2023/10/28

Image processing system and method

2023/1/19

Unsupervised path regression networks

2021/9/27

Daniel Lenton
Daniel Lenton

H-Index: 1

Ronald Clark
Ronald Clark

H-Index: 13

Waypoint planning networks

arXiv preprint arXiv:2105.00312

2021/5/1

End-to-end egospheric spatial memory

arXiv preprint arXiv:2102.07764

2021/2/15

Ivy: Templated deep learning for inter-framework portability

arXiv preprint arXiv:2102.02886

2021/2/4

Learning To Find Shortest Collision-Free Paths From Images.

CoRR

2020

Daniel Lenton
Daniel Lenton

H-Index: 1

Ronald Clark
Ronald Clark

H-Index: 13

Morefusion: Multi-object reasoning for 6d pose estimation from volumetric fusion

2020

See List of Professors in Daniel Lenton University(Imperial College London)

Co-Authors

academic-engine