Results 211 to 220 of about 4,274,126 (325)

Applying computer vision to accelerate monitoring and analysis of bird incubation behaviors: a case study using common eider nest camera footage

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
Visualization of the pipeline is divided into two primary segments: automated (i.e., the user adapts the code directly to build a custom computer vision model) and human‐in‐the‐loop (i.e., the user manually evaluates the output of the model). In step 1, raw imagery data are selected for training and testing datasets; ideally, these datasets are ...
Lindsay Veazey   +3 more
wiley   +1 more source

Covariates influence optimal camera‐trap survey design for occupancy modelling

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
We investigated the impact of covariates (e.g., habitat quality, temperature) on the optimal design of camera trap surveys to estimate species occupancy. Using simulations of a virtual species, we found that increasing the number of cameras consistently reduced error across a range of covariate effects.
Owain Barton   +4 more
wiley   +1 more source

On optimal foraging and multi-armed bandits

open access: yesAllerton Conference on Communication, Control, and Computing, 2013
Vaibhav Srivastava   +2 more
semanticscholar   +1 more source

A UAV‐based deep learning pipeline for intertidal macrobenthos monitoring: Behavioral and age classification in Tachypleus tridentatus

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
The endangered tri‐spine horseshoe crab (Tachypleus tridentatus), a “living fossil” crucial to coastal ecology and biomedical research, is experiencing severe population declines. Effective conservation requires efficient monitoring, which traditional methods cannot deliver at scale. We develop an integrated UAV deep learning framework tailored to this
Xiaohai Chen   +7 more
wiley   +1 more source

Human foraging strategies flexibly adapt to resource distribution and time constraints. [PDF]

open access: yesCogn Affect Behav Neurosci
Simonelli V   +3 more
europepmc   +1 more source

To eat and not be eaten: optimal foraging behaviour in suspension feeding copepods

open access: yesJournal of the Royal Society Interface, 2013
T. Kiørboe, Houshuo Jiang
semanticscholar   +1 more source

Comparing convolutional neural network and random forest for benthic habitat mapping in Apollo Marine Park

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
A comparison of Convolutional Neural Network (CNN) and Random Forest (RF) model predictions of benthic habitats within Apollo Marine Park. The CNN (left) and RF (right) classification maps show the spatial distribution of three habitat types: high energy circalittoral rock with seabed‐covering sponges, low complexity circalittoral rock with non‐crowded
Henry Simmons   +6 more
wiley   +1 more source

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