Recognition of European mammals and birds in camera trap images using deep neural networks [PDF]
IET Computer VisionMost machine learning methods for animal recognition in camera trap images are limited to mammal identification and group birds into a single class. Machine learning methods for visually discriminating birds, in turn, cannot discriminate between mammals ...
Daniel Schneider +5 more
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CAMERA – Mobility Report 1 [PDF]
, 2019 This report is a result of research performed so far in the scope of the CAMERA Coordination and Support Action (CSA). In CAMERA, we investigate research initiatives from the past decade that focus on the European air transport system and its integration
Cook, A.J. +2 more
core +6 more sources
Camera trapping and spatially explicit capture–recapture for the monitoring and conservation management of lions: Insights from a globally important population in Tanzania [PDF]
, 2022 1. Accurate and precise estimates of population status are required to inform and evaluate conservation management and policy interventions. Although the lion (Panthera leo) is a charismatic species receiving increased conservation attention, robust ...
Smit, Josephine B +15 more
core +1 more source
Component processes of detection probability in camera-trap studies: understanding the occurrence of false-negatives [PDF]
, 2020 Camera-trap studies in the wild record true-positive data, but data loss from false-negatives (i.e. an animal is present but not recorded) is likely to vary and widely impact data quality.
White, Patrick J. C. +2 more
core +1 more source
, 2020 The a) plan view and b) profile view of the camera trap station setup. Components are: A, drift fence (~30 x ~300 cm); B, cork floor tile (30 x 30 x 0.6 cm); C, passive infrared (PIR) detection bands to demonstrate orientation; D, Reconyx HC600 camera ...
Frederick Ford (8313726) +3 more
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Camera Trap Monitoring for Wildlife Density Estimation with the REST Model: A Handbook Focusing on Rainforest Mammals [PDF]
, 2022 This handbook is a product of an international joint research initiative between Cameroon and Japan funded by JST/JICA SATREPS (JPMJSA1702) and JSPS KAKENHI (JP18K14803, JP 20KK0015, JP21K15173).Earlier handbook version (Hongo et al.
HONGO, Shun, YAJIMA, Gota
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Camera Trap Images used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science" [PDF]
, 2018 All images were downloaded from Zooniverse and have been resized to 330x330 pixels.This dataset provides the camera trap images used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science" as well as meta-data about
Boyer, Amy +7 more
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Datasets for Robust ecological analysis of camera trap data labelled by a machine learning model
, 2021 These data accompany Whytock and Swiezewski et al. 2021. Robust ecological analysis of camera trap data labelled by a machine learning model. There are six .csv files in total with information on the species identified in camera trap images and the ...
Orbell, Christopher, Whytock, Robin
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An evidence-based approach to identifying resting sites of Eurasian otter (Lutra lutra) from camera-trap and field-sign data [PDF]
, 2023 Mammals' resting sites (dens) are important features of their ecology. Eurasian otter Lutra lutra resting sites are strictly protected by UK and European legislation and are ostensibly identified from associated field-signs. This legislation is difficult
Briers, Robert A. +7 more
core +1 more source
Climate Change Ecology, 2021 Climate change will accelerate the extinction rate of wildlife species in the Anthropocene. Identifying which species exhibit the capacity to be flexible in their activity patterns to avoid heat stress will help direct conservation effort to those ...
Richard Buchholz +2 more
doaj +1 more source