Identifying animal species in camera trap images using deep learning and citizen science

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

A systematic study of the class imbalance problem in convolutional neural networks

(2018) Mateusz Buda et al.   NEURAL NETWORKS

A generalized approach for producing, quantifying, and validating citizen science data from wildlife images

(2016) Alexandra Swanson et al.   CONSERVATION BIOLOGY

Animal Detection From Highly Cluttered Natural Scenes Using Spatiotemporal Object Region Proposals and Patch Verification

(2016) Zhi Zhang et al.   IEEE TRANSACTIONS ON MULTIMEDIA

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna

(2015) Alexandra Swanson et al.   Scientific Data

Automated identification of animal species in camera trap images

(2013) Xiaoyuan Yu et al.   EURASIP Journal on Image and Video Processing

Citizen Science as an Ecological Research Tool: Challenges and Benefits

(2010) Janis L. Dickinson et al.   Annual Review of Ecology Evolution and Systematics

A new dawn for citizen science

(2009) Jonathan Silvertown   TRENDS IN ECOLOGY & EVOLUTION