… the target function for image classification regarding to specific objects size ratio. In our
work, we apply Tensor Networks to solve this arising tough machine learning problem. First, we …

… how to apply these concepts to a quantum computer in §3 … (a) Formally, the task of classification
is performed by some … tackled with current quantum algorithms has to be small. Instead, …

… Circuit design for quantum machine learning remains a … applications of tensor network quantum
circuits by applying … path toward executing large circuits using small quantum computers. …

… Machine learning is a promising application of quantum … perform handwriting recognition
using a hybrid quantum-classical … Tensor network models could be implemented on small, near…

… the class decision in a small-dimensional quantum register. We … In our quantum approach
to TTN-based classification, we … -based machine learning beyond image data, we also apply …

… of tensor network models in a current machine learning … In quantum physics, the success of
tensor networks such as … the methodology of applying tensor networks to supervised learning, …

… To further test our proposal, we apply our method on the images of nerve cord for the purpose
of unsupervised segmentation. [35] We take just one of the images and split it into (24 × 24…

… quantum tensor network methods for machine learning is to … so that we may apply the
same tensor network structure to … circuits (or equivalently small tensor networks of low bond …

… The tensor network approach has wild application areas both in quantum physics and machine
learning [… gate is a basic element, which operates on a small number of quantum bits [37]. …

… classification domain of object detection, quantum learning … quantum-gates-based fabricated
system of quantum volume (4096) and rise of explainable domain of study in deep learning …