Quantum machine learning techniques have been proposed as a way to potentially enhance performance in applications. In this paper, we introduce two new quantum methods for neural networks. The first one is orthogonal network, which based on pyramidal circuit the building block implementing matrix multiplication. We provide an efficient training such networks; novel algorithms are detailed both ...

Modeling low level features to high semantics in medical imaging is an important aspect filtering anatomy objects. Bag of Visual Words (BOVW) representations have been proven effective model these mid representations. Convolutional neural nets are learning systems that can automatically extract high-quality from raw images. However, their deployment the field still a bit challenging due lack tr...

This paper aims to propose a tool for image classification in medical diagnosis decision support, context where computational power is limited and then specific, high-speed computing infrastructures cannot be used (mainly economic energy consuming reasons). The proposed method combines deep neural networks algorithm with imaging procedures implemented allow an efficient use on affordable hardwa...