Automating the Analysis of Fish Abundance Using Object Detection: Optimizing Animal Ecology With Deep Learning

A comparison of deep learning and citizen science techniques for counting wildlife in aerial survey images

(2019) Colin J. Torney et al.   Methods in Ecology and Evolution

Automatic fish detection in underwater videos by a deep neural network-based hybrid motion learning system

(2019) Ahmad Salman et al.   ICES JOURNAL OF MARINE SCIENCE

Automated identification of benthic epifauna with computer vision

(2019) N Piechaud et al.   MARINE ECOLOGY PROGRESS SERIES

The Role of Vegetated Coastal Wetlands for Marine Megafauna Conservation

(2019) Michael Sievers et al.   TRENDS IN ECOLOGY & EVOLUTION

ERISNet: deep neural network for Sargassum detection along the coastline of the Mexican Caribbean

(2019) Javier Arellano-Verdejo et al.   PeerJ

Drones and convolutional neural networks facilitate automated and accurate cetacean species identification and photogrammetry

(2019) Patrick C. Gray et al.   Methods in Ecology and Evolution

Improving Pantanal fish species recognition through taxonomic ranks in convolutional neural networks

(2019) Anderson Aparecido dos Santos et al.   Ecological Informatics

Camera field-of-view and fish abundance estimation: A comparison of individual-based model output and empirical data

(2018) Matthew D. Campbell et al.   JOURNAL OF EXPERIMENTAL MARINE BIOLOGY AND ECOLOGY

Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning

(2018) Mohammad Sadegh Norouzzadeh et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Futurecasting ecological research: the rise of technoecology

(2018) Blake M. Allan et al.   Ecosphere

A Deep learning method for accurate and fast identification of coral reef fishes in underwater images

(2018) Sébastien Villon et al.   Ecological Informatics

Umbrellas can work under water: Using threatened species as indicator and management surrogates can improve coastal conservation

(2017) Ben L. Gilby et al.   ESTUARINE COASTAL AND SHELF SCIENCE

A computer vision for animal ecology

(2017) Ben G. Weinstein   JOURNAL OF ANIMAL ECOLOGY

Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

(2017) Waseem Rawat et al.   NEURAL COMPUTATION

Ten quick tips for machine learning in computational biology

(2017) Davide Chicco   BioData Mining

StingerCam: A tool for ecologists and stakeholders to detect the presence of venomous tropical jellyfish

(2016) L. E. Llewellyn et al.   LIMNOLOGY AND OCEANOGRAPHY-METHODS

Fish species classification in unconstrained underwater environments based on deep learning

(2016) Ahmad Salman et al.   LIMNOLOGY AND OCEANOGRAPHY-METHODS

Harmful effects of sediment-induced turbidity on juvenile fish in estuaries

(2015) ML Lowe et al.   MARINE ECOLOGY PROGRESS SERIES

Deep learning

(2015) Yann LeCun et al.   NATURE

Opinion: Reproducible research can still be wrong: Adopting a prevention approach: Fig. 1.

(2015) Jeffrey T. Leek et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Spatial and temporal changes in cumulative human impacts on the world’s ocean

(2015) Benjamin S. Halpern et al.   Nature Communications

Harmful effects of sediment-induced turbidity on juvenile fish in estuaries

(2015) ML Lowe et al.   MARINE ECOLOGY PROGRESS SERIES

Connectivity networks reveal the risks of crown-of-thorns starfish outbreaks on the Great Barrier Reef

(2014) Karlo Hock et al.   JOURNAL OF APPLIED ECOLOGY

A Herbivore Knows Its Patch: Luderick, Girella tricuspidata, Exhibit Strong Site Fidelity on Shallow Subtidal Reefs in a Temperate Marine Park

(2013) Adrian M. Ferguson et al.   PLoS One

Unmanned Aerial Vehicles (UAVs) for Surveying Marine Fauna: A Dugong Case Study

(2013) Amanda Hodgson et al.   PLoS One

The Pascal Visual Object Classes (VOC) Challenge

(2009) Mark Everingham et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Accelerating loss of seagrasses across the globe threatens coastal ecosystems

(2009) M. Waycott et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA