Quantum machine learning for image classification
A Senokosov, A Sedykh, A Sagingalieva… - Machine Learning …, 2024 - iopscience.iop.org
Image classification, a pivotal task in multiple industries, faces computational challenges
due to the burgeoning volume of visual data. This research addresses these challenges by …
due to the burgeoning volume of visual data. This research addresses these challenges by …
Hybrid quantum neural network for drug response prediction
Simple Summary This work successfully employs a novel approach in processing patient
and drug data to predict the drug response for cancer patients. The approach uses a deep …
and drug data to predict the drug response for cancer patients. The approach uses a deep …
An exponentially-growing family of universal quantum circuits
Quantum machine learning has become an area of growing interest but has certain
theoretical and hardware-specific limitations. Notably, the problem of vanishing gradients, or …
theoretical and hardware-specific limitations. Notably, the problem of vanishing gradients, or …
Parallel hybrid networks: an interplay between quantum and classical neural networks
The use of quantum neural networks for machine learning is a paradigm that has recently
attracted considerable interest. Under certain conditions, these models approximate the …
attracted considerable interest. Under certain conditions, these models approximate the …
A supervised hybrid quantum machine learning solution to the emergency escape routing problem
N Haboury, M Kordzanganeh, S Schmitt… - ar**
Y Chen, X Shen, G Zhang, Z Lu - Remote Sensing, 2023 - mdpi.com
With satellite quantity and quality development in recent years, remote sensing products in
vast areas are becoming widely used in more and more fields. The acquisition of large …
vast areas are becoming widely used in more and more fields. The acquisition of large …
Hybrid quantum ResNet for car classification and its hyperparameter optimization
Image recognition is one of the primary applications of machine learning algorithms.
Nevertheless, machine learning models used in modern image recognition systems consist …
Nevertheless, machine learning models used in modern image recognition systems consist …
Hybrid quantum image classification and federated learning for hepatic steatosis diagnosis
L Lusnig, A Sagingalieva, M Surmach, T Protasevich… - Diagnostics, 2024 - mdpi.com
In the realm of liver transplantation, accurately determining hepatic steatosis levels is crucial.
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …