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Deep Learning 101

Aivia uses a wide range of AI techniques (e.g. random forest, support vector machines and deep learning) to solve image-related tasks. For more demanding applications, Aivia uses a specific type of deep learning, known as fully convolutional neural networks (CNN).

CNNs are particularly well-suited for capturing non-linear relationships between large volumes of paired image sets (e.g. raw image and manually annotated image in the case of image segmentation tasks) thus allowing for a level of accuracy that rivals human experts (1,2).


A neural network is composed of multiple artificial "neurons" organized in interconnected layers. Similarly to their biological counterparts, the neurons in artificial neural networks respond to specific stimuli, image patterns or features.



When stimulated, a neuron (both real and artificial) affects connected neurons in deeper layers until the output layer is reached where a prediction is made.