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Automatic Recognition of Mammal Genera on Camera-Trap Images using Multi-Layer Robust Principal Component Analysis and Mixture Neural Networks
The segmentation and classification of animals from camera-trap images is due to the conditions under which the images are taken, a difficult task.
Camera-trap images segmentation using multi-layer robust principal component analysis
Our method computes sparse and low-rank images from a weighted sum of descriptors, using color and texture features as case of study for camera-trap images segmentation.
Automatic Identification of Scenedesmus Polymorphic Microalgae from Microscopic Images
Microalgae counting is used to measure biomass quantity.
Towards Automatic Wild Animal Monitoring: Identification of Animal Species in Camera-trap Images using Very Deep Convolutional Neural Networks
Non intrusive monitoring of animals in the wild is possible using camera trapping framework, which uses cameras triggered by sensors to take a burst of images of animals in their habitat.
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