Results 71 to 80 of about 296,091 (283)

Quantum Computing Meets Deep Learning: A Promising Approach for Diabetic Retinopathy Classification

Mathematics, 2023
Diabetic retinopathy seems to be the cause of micro-vascular retinal alterations. It remains a leading reason for blindness and vision loss in adults around the age of 20 to 74.
Shtwai Alsubai, Abdullah Alqahtani, Adel Binbusayyis, Mohemmed Sha, Abdu Gumaei, Shuihua Wang   +5 more
doaj   +1 more source

Quasi-Quantum Planes and Quasi-Quantum Groups of Dimension $p^3$ and $p^4$ [PDF]

, 2014
The aim of this paper is to contribute more examples and classification results of finite pointed quasi-quantum groups within the quiver framework initiated in \cite{qha1, qha2}.
Huang, Hua-Lin, Yang, Yuping
core  

Quantum teardrops

, 2011
Algebras of functions on quantum weighted projective spaces are introduced, and the structure of quantum weighted projective lines or quantum teardrops are described in detail.
A. Connes, A.J.-L. Sheu, D. Auroux, E. Hawkins, F. D’Andrea, H.-J. Schneider, J.H. Hong, L. Da̧browski, P.M. Hajac, P.M. Hajac, P.M. Hajac, P.M. Hajac, S.L. Woronowicz, S.L. Woronowicz, Simon A. Fairfax, T. Brzeziński, T. Brzeziński, T. Masuda, Tomasz Brzeziński, U. Meyer   +19 more
core   +1 more source

Photoswitching Conduction in Framework Materials

Advanced Functional Materials, EarlyView.
This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez, Stefan Hecht, Wolfgang Wenzel, Lars Heinke, Mariana Kozlowska   +4 more
wiley   +1 more source

Quantum Text Encoding for Classification Tasks

2022 IEEE/ACM 7th Symposium on Edge Computing (SEC), 2022
This paper explores text classification on quantum computers. Previous results have achieved perfect accuracy on an artificial dataset of 100 short sentences, but at the unscalable cost of using a qubit for each word. This paper demonstrates that an amplitude encoded feature map combined with a quantum support vector machine can achieve 62% average ...
Aaranya Alexander, Dominic Widdows
openaire   +2 more sources

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Quantum-inspired classification based on quantum state discrimination [PDF]

Quantum Machine Intelligence
19 pages, 4 ...
Zambrini Cruzeiro, Emmanuel, De Mol, Christine, Massar, Serge, Pironio, Stefano   +3 more
openaire   +3 more sources

Auto‐Generated Valence States in Electrocatalysts for Boosting Oxygen and Hydrogen Evolution Kinetics in Alkaline Water/Alkaline Seawater/Simulated Seawater/Natural Seawater

Advanced Functional Materials, EarlyView.
This review systematically highlights the latest achievements in mixed‐valence states relevant to hydrogen and oxygen evolution reactions, providing essential insights into future directions and methods for large‐scale practical implementation. This critical review is expected to provide an overview of recent advancements in diverse valence‐state metal
Jitendra N. Tiwari, Gokul Bhaskaran, Krishan Kumar, Yun Suk Huh, Young‐Kyu Han   +4 more
wiley   +1 more source

Quantum Discriminant Analysis for Dimensionality Reduction and Classification

, 2016
We present quantum algorithms to efficiently perform discriminant analysis for dimensionality reduction and classification over an exponentially large input data set.
Cong, Iris, Duan, Luming
core   +1 more source

Quantum autoencoders for image classification

Quantum Machine Intelligence
Classical machine learning often struggles with complex, high-dimensional data. Quantum machine learning offers a potential solution, promising more efficient processing. The quantum convolutional neural network (QCNN), a hybrid algorithm, fits current noisy intermediate-scale quantum hardware.
Hinako Asaoka, Kazue Kudo
openaire   +2 more sources