A work on processing techniques using Deep Learning (Convolutional Neural Networks) to detect and classify marine mammals in aerial photographs. The computational capacity offered by these new tools will allow the scientific community to better study endangered species and to give an adequate and rapid response to face the current biodiversity crisis. For this project there isn’t much of a problem to solve but an opportunity to improve. Improve upon the project that was left which tried to choose the appropriate architecture, build a completely new dataset and figure out what are the best parameters in order to achieve certain goals
Authors thank the Bureau of Ocean Energy Management for the funding of MARU deployments, Excelerate ...
The implementation of intelligent software to identify and classify objects and individuals in visua...
Despite current efforts to study deep-sea life, there is a dependency on technological advancements ...
Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can gener...
The Monterey Bay Aquarium Research Institute routinely deploys remotely operated underwater vehicles...
In recent years, the application of machine learning and remote sensing technologies in wildlife con...
An active research on flora and fauna is carried out since last few decades. We have focused on anal...
With the availability of low-cost and efficient digital cameras, ecologists can now survey the world...
Motion Triggered Wildlife Camera traps are rapidly being used to remotely track animals and help per...
Deep learning has become a key tool for the automated monitoring of animal populations with video-su...
An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the g...
International audienceLarge land and ocean mammals, like elephants and whales, play essential roles ...
Master's thesis in Computer scienceWith the use of very high resolution (VHR) satellite images we ca...
International audienceProcessing data from surveys using photos or videos remains a major bottleneck...
Having accurate, detailed, and upto-date information about wildlife location and behavior across bro...
Authors thank the Bureau of Ocean Energy Management for the funding of MARU deployments, Excelerate ...
The implementation of intelligent software to identify and classify objects and individuals in visua...
Despite current efforts to study deep-sea life, there is a dependency on technological advancements ...
Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can gener...
The Monterey Bay Aquarium Research Institute routinely deploys remotely operated underwater vehicles...
In recent years, the application of machine learning and remote sensing technologies in wildlife con...
An active research on flora and fauna is carried out since last few decades. We have focused on anal...
With the availability of low-cost and efficient digital cameras, ecologists can now survey the world...
Motion Triggered Wildlife Camera traps are rapidly being used to remotely track animals and help per...
Deep learning has become a key tool for the automated monitoring of animal populations with video-su...
An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the g...
International audienceLarge land and ocean mammals, like elephants and whales, play essential roles ...
Master's thesis in Computer scienceWith the use of very high resolution (VHR) satellite images we ca...
International audienceProcessing data from surveys using photos or videos remains a major bottleneck...
Having accurate, detailed, and upto-date information about wildlife location and behavior across bro...
Authors thank the Bureau of Ocean Energy Management for the funding of MARU deployments, Excelerate ...
The implementation of intelligent software to identify and classify objects and individuals in visua...
Despite current efforts to study deep-sea life, there is a dependency on technological advancements ...