S. Lopez‐Marcano

发表

Fish surveys on the move: Adapting automated fish detection and classification frameworks for videos on a remotely operated vehicle in shallow marine waters

R. Connolly, K. I. Jinks, C. Herrera, 2022, Frontiers in Marine Science.

Supplementary report to the final report of the coral reef expert group: S6. Novel technologies in coral reef monitoring

M. González-Rivero, T. Bridge, R. Babcock, 2020 .

Monitoring of Coral Reefs Using Artificial Intelligence: A Feasible and Cost-Effective Approach

Oscar Beijbom, Alberto Rodriguez-Ramirez, Manuel González-Rivero, 2020, Remote. Sens..

Automatic detection of fish and tracking of movement for ecology

B. Kusy, R. Connolly, C. Brown, 2021, Ecology and evolution.

Coral composition and bottom-wave metrics improve understanding of the patchiness of cyclone damage on reefs.

A. Rodriguez-Ramirez, M. González-Rivero, O. Hoegh-Guldberg, 2022, The Science of the total environment.

Fine-scale time series surveys reveal new insights into spatio-temporal trends in coral cover (2002–2018), of a coral reef on the Southern Great Barrier Reef

S. Phinn, C. Roelfsema, A. Rodriguez-Ramirez, 2021, Coral Reefs.

Multi-scale estimation of the effects of pressures and drivers on mangrove forest loss globally

Vivitskaia J. D. Tulloch, R. Connolly, C. Brown, 2020 .

Coral Reef Community Changes in Karimunjawa National Park, Indonesia: Assessing the Efficacy of Management in the Face of Local and Global Stressors

Ambariyanto, Dominic E. P. Bryant, Catherine J. S. Kim, 2020 .

A contemporary baseline record of the world’s coral reefs

Dominic E. P. Bryant, Catherine J. S. Kim, P. Dalton, 2020, Scientific data.

Fish use of restored mangroves matches that in natural mangroves regardless of forest age

R. Connolly, M. Sievers, S. Lopez‐Marcano, 2022, Restoration Ecology.

Annotated Video Footage for Automated Identification and Counting of Fish in Unconstrained Seagrass Habitats

Ellen M. Ditria, R. Connolly, E. Jinks, 2021, Frontiers in Marine Science.

Improved accuracy for automated counting of a fish in baited underwater videos for stock assessment

G. Jackson, Elizabeth Jinks, RM Connolly, 2021, bioRxiv.

Automating the analysis of fish abundance using object detection: optimising animal ecology with deep learning

Michael Sievers, Christopher J. Brown, Sebastian Lopez-Marcano, 2019, bioRxiv.

Deep learning for automated analysis of fish abundance: the benefits of training across multiple habitats

Ellen M. Ditria, Eric L. Jinks, R. Connolly, 2020, bioRxiv.

Benthic and coral reef community field data for Heron Reef, Southern Great Barrier Reef, Australia, 2002–2018

S. Phinn, C. Roelfsema, A. Rodriguez-Ramirez, 2021, Scientific data.

The slow rise of technology: Computer vision techniques in fish population connectivity

Michael Sievers, Christopher J. Brown, Sebastian Lopez-Marcano, 2020, Aquatic Conservation: Marine and Freshwater Ecosystems.

Automating the analysis of fish abundance using object detection: optimising animal ecology with deep learning

Christopher J. Brown, Sebastian Lopez-Marcano, Rod M. Connolly, 2019, bioRxiv.

Estimating enhanced fish production on restored shellfish reefs using automated data collection from underwater videos

M. Sievers, R. Baring, K. I. Jinks, 2024, Journal of Applied Ecology.