Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
Browse
Publications
Preprints
About
About UCL Open: Env.
Aims and Scope
Editorial Board
Indexing
APCs
How to cite
Publishing policies
Editorial policy
Peer review policy
Equality, Diversity & Inclusion
About UCL Press
Contact us
For authors
Information for authors
How it works
Benefits of publishing with us
Submit
How to submit
Preparing your manuscript
Article types
Open Data
ORCID
APCs
Contributor agreement
For reviewers
Information for reviewers
Review process
How to peer review
Peer review policy
My ScienceOpen
Sign in
Register
Dashboard
Search
2
views
36
references
Top references
cited by
0
Cite as...
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
2,696
similar
All similar
Record
: found
Abstract
: not found
Book Chapter
: not found
Artificial Intelligence Oceanography
Benthic Organism Detection, Quantification and Seamount Biology Detection Based on Deep Learning
other
Author(s):
Yuhai Liu
,
Yu Xu
,
Haining Wang
,
Xiaofeng Li
Publication date
(Online):
February 04 2023
Publisher:
Springer Nature Singapore
Read this book at
Publisher
Buy book
Review
Review book
Invite someone to review
Bookmark
Cite as...
There is no author summary for this book yet. Authors can add summaries to their books on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
Computer Vision, Deep Learning, Deep Reinforcement Learning, IoT
Most cited references
36
Record
: found
Abstract
: not found
Conference Proceedings
: not found
Deep Residual Learning for Image Recognition
Kaiming He
,
Xiangyu Zhang
,
Shaoqing Ren
…
(2020)
0
comments
Cited
8951
times
– based on
0
reviews
Bookmark
Record
: found
Abstract
: not found
Article
: not found
Support-vector networks
Corinna Cortes
,
Vladimir Vapnik
(1995)
0
comments
Cited
3181
times
– based on
0
reviews
Review now
Bookmark
Record
: found
Abstract
: not found
Article
: not found
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
,
Jia Deng
,
Jiang-hao Su
…
(2015)
0
comments
Cited
2804
times
– based on
0
reviews
Review now
Bookmark
All references
Author and book information
Book Chapter
Publication date (Print):
2023
Publication date (Online):
February 04 2023
Pages
: 323-346
DOI:
10.1007/978-981-19-6375-9_16
SO-VID:
96715260-10e0-493e-9736-1c170552feac
History
Data availability:
Comments
Comment on this book
Sign in to comment
Book chapters
pp. 1
Artificial Intelligence Foundation of Smart Ocean
pp. 45
Forecasting Tropical Instability Waves Based on Artificial Intelligence
pp. 63
Sea Surface Height Anomaly Prediction Based on Artificial Intelligence
pp. 83
Satellite Data-Driven Internal Solitary Wave Forecast Based on Machine Learning Techniques
pp. 105
AI-Based Subsurface Thermohaline Structure Retrieval from Remote Sensing Observations
pp. 125
Ocean Heat Content Retrieval from Remote Sensing Data Based on Machine Learning
pp. 147
Detecting Tropical Cyclogenesis Using Broad Learning System from Satellite Passive Microwave Observations
pp. 165
Tropical Cyclone Monitoring Based on Geostationary Satellite Imagery
pp. 189
Reconstruction of pCO\(_{2}\) Data in the Southern Ocean Based on Feedforward Neural Network
pp. 209
Detection and Analysis of Mesoscale Eddies Based on Deep Learning
pp. 227
Deep Convolutional Neural Networks-Based Coastal Inundation Mapping from SAR Imagery: with One Application Case for Bangladesh, a UN-defined Least Developed Country
pp. 253
Sea Ice Detection from SAR Images Based on Deep Fully Convolutional Networks
pp. 277
Detection and Analysis of Marine Green Algae Based on Artificial Intelligence
pp. 287
Automatic Waterline Extraction of Large-Scale Tidal Flats from SAR Images Based on Deep Convolutional Neural Networks
pp. 303
Extracting Ship’s Size from SAR Images by Deep Learning
pp. 323
Benthic Organism Detection, Quantification and Seamount Biology Detection Based on Deep Learning
Similar content
2,696
A Review of the Effects of Seamounts on Biological Processes
Authors:
George Boehlert
,
Amatzia Genin
Modelled effects of primary and secondary production enhancement by seamounts on local fish stocks
Authors:
Cathy M Bulman
,
Telmo Morato
,
Tony Pitcher
Physiography of the Orca Seamount in the Bransfield Strait, Antarctic peninsula.
Authors:
J Hatzky
See all similar