Forest fire surveillance systems: A review of deep learning methods
This review aims to critically examine the existing state-of-the-art forest fire detection
systems that are based on deep learning methods. In general, forest fire incidences bring …
systems that are based on deep learning methods. In general, forest fire incidences bring …
Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning
Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively
impacts populations, erodes wildlife conservation, drains resource dollars, and challenges …
impacts populations, erodes wildlife conservation, drains resource dollars, and challenges …
Comparing fine-grained and coarse-grained object detection for ecology
Computer vision applications are increasingly popular for wildlife monitoring tasks. While
some studies focus on the monitoring of a single species, such as a particular endangered …
some studies focus on the monitoring of a single species, such as a particular endangered …
Multi-Object Tracking in Heterogeneous environments (MOTHe) for animal video recordings
Aerial imagery and video recordings of animals are used for many areas of research such as
animal behaviour, behavioural neuroscience and field biology. Many automated methods …
animal behaviour, behavioural neuroscience and field biology. Many automated methods …
[PDF][PDF] Track Recognition via Artificial Cognition (TRAC): Preliminary Report on the Application of Machine Learning to Identify Dinosaur Tracks
PC Murphey, A Romilio, NA Matthews… - New Mexico Museum …, 2024 - researchgate.net
Despite the utilization of new technologies to objectively record and document dinosaur
tracks in the field, the categorization and identification of dinosaur tracks remains a largely …
tracks in the field, the categorization and identification of dinosaur tracks remains a largely …