[HTML][HTML] Perspectives in machine learning for wildlife conservation
Inexpensive and accessible sensors are accelerating data acquisition in animal ecology.
These technologies hold great potential for large-scale ecological understanding, but are …
These technologies hold great potential for large-scale ecological understanding, but are …
Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …
promises significant advances to support the Sustainable Development Goals (SDGs). New …
WilDect-YOLO: An efficient and robust computer vision-based accurate object localization model for automated endangered wildlife detection
Objective. With climatic instability, various ecological disturbances, and human actions
threaten the existence of various endangered wildlife species. Therefore, an up-to-date …
threaten the existence of various endangered wildlife species. Therefore, an up-to-date …
Detecting mammals in UAV images: Best practices to address a substantially imbalanced dataset with deep learning
Abstract Knowledge over the number of animals in large wildlife reserves is a vital necessity
for park rangers in their efforts to protect endangered species. Manual animal censuses are …
for park rangers in their efforts to protect endangered species. Manual animal censuses are …
Growing status observation for oil palm trees using Unmanned Aerial Vehicle (UAV) images
For both the positive economic benefit and the negative ecological impact of the rapid
expansion of oil palm plantations in tropical developing countries, it is significant to achieve …
expansion of oil palm plantations in tropical developing countries, it is significant to achieve …
Monitoring biodiversity in the Anthropocene using remote sensing in species distribution models
CF Randin, MB Ashcroft, J Bolliger… - Remote sensing of …, 2020 - Elsevier
In the face of the growing challenges brought about by human activities, effective planning
and decision-making in biodiversity and ecosystem conservation, restoration, and …
and decision-making in biodiversity and ecosystem conservation, restoration, and …
[HTML][HTML] Automated cattle counting using Mask R-CNN in quadcopter vision system
The accurate and reliable counting of animals in quadcopter acquired imagery is one of the
most promising but challenging tasks in intelligent livestock management in the future. In this …
most promising but challenging tasks in intelligent livestock management in the future. In this …
Automated detection of wildlife using drones: Synthesis, opportunities and constraints
E Corcoran, M Winsen, A Sudholz… - Methods in Ecology …, 2021 - Wiley Online Library
Accurate detection of individual animals is integral to the management of vulnerable wildlife
species, but often difficult and costly to achieve for species that occur over wide or …
species, but often difficult and costly to achieve for species that occur over wide or …
Applications, databases and open computer vision research from drone videos and images: a survey
Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an
emerging application attracting significant attention from researchers in various areas of …
emerging application attracting significant attention from researchers in various areas of …
Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape
New satellite remote sensing and machine learning techniques offer untapped possibilities
to monitor global biodiversity with unprecedented speed and precision. These efficiencies …
to monitor global biodiversity with unprecedented speed and precision. These efficiencies …