Search Results - Quantum convolutional autoencoder

Optimal satellite selection using quantum convolutional autoencoder for low-cost GNSS receiver applications

Authors: Nalineekumari Arasavali Mogadala Vinod Kumar Sasibhushana Rao Gottapu et al.

Source: Sci Rep
Scientific Reports, Vol 15, Iss 1, Pp 1-17 (2025)

Subject Terms: Quantum convolutional autoencoder, GNSS, Science, Satellite selection, Combined constellation, Sustainable Development Goal (SDG) 9:Industry, Innovation, and Infrastructure, SDG 11: Sustainable Cities and Communities, Medicine, Article

Access URL: https://pubmed.ncbi.nlm.nih.gov/40082537
https://doaj.org/article/baf00827405b4ae7bdeb1dbfabf77448

Quantum Circuits for Quantum Convolutions: A Quantum Convolutional Autoencoder

Authors: Orduz, Javier Rivas, Pablo Baker, Erich

Subject Terms: Machine Learning, FOS: Computer and information sciences, Quantum Physics, FOS: Physical sciences, Quantum Physics (quant-ph), I.2.6, F.1.2, Machine Learning (cs.LG), 81P68, 68T07

Access URL: http://arxiv.org/abs/2509.00637

Enhancing a convolutional autoencoder with a quantum approximate optimization algorithm for image noise reduction

Authors: Tara Kit Kimsay Pov Kimleang Kea et al.

Source: Machine Learning: Science and Technology, Vol 6, Iss 4, p 045027 (2025)

Subject Terms: quantum computing, quantum convolutional autoencoder, variational quantum algorithm, quantum machine learning, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://doaj.org/toc/2632-2153

Access URL: https://doaj.org/article/4efa9a37709b46e288463e3f8e36321f

Comparative Analysis of Quantum and Classical Convolutional Autoencoders on the MNIST Dataset

Additional Titles: Komparativ analys av kvantiska och klassiska konvolutionerande autokodare på MNIST datasetet

Authors: Astorga Castillo, Dante Friman, Lukas

Index Terms: Quantum computing, Quantum neural network, Quantum machine learning, Convolutional autoencoder, Quantum convolutional autoencoder, Quanvolution, Quanvolutional autoencoder, Kvantberäkning, Kvantneurala nätverk, Kvantmaskininlärning, Konvolutionerande autokodare, Kvantkonvolutionerande autokodare, Computer and Information Sciences, Data- och informationsvetenskap, Student thesis, info:eu-repo/semantics/bachelorThesis, text

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-351190
TRITA-EECS-EX ; 2024:389

Enhancing a Convolutional Autoencoder with a Quantum Approximate Optimization Algorithm for Image Noise Reduction

Authors: Kea, Kimleang Chang, Won-Du Park, Hee Chul et al.

Subject Terms: Quantum Physics

Access URL: http://arxiv.org/abs/2401.06367

A QUANTUM CONVOLUTION AUTOENCODER FOR HANDWRITTEN LETTERS AND DIGITS: A CASE STUDY.

Authors: SAWERWAIN, MAREK KOWAL, MAREK KORBICZ, JÓZEF

Source: International Journal of Applied Mathematics & Computer Science; 2025, Vol. 35 Issue 4, p651-666, 16p

Enhancing a convolutional autoencoder with a quantum approximate optimization algorithm for image noise reduction.

Authors: Kit, Tara Pov, Kimsay Kea, Kimleang et al.

Source: Machine Learning: Science & Techonology; 2025, Vol. 6 Issue 4, p1-15, 15p

QCAE-QOC-SVM: A hybrid quantum machine learning model for DoS and Fuzzy attack detection on autonomous vehicle CAN bus

Authors: Meghana R Sowmyashree Sakrepatna Ramesha Adwitiya Mukhopadhyay

Source: MethodsX, Vol 15, Iss , Pp 103471- (2025)

Subject Terms: A hybrid of Quantum Convolutional Autoencoder and Quantum Orthogonal Classifier with SVM, Science

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2215016125003164; https://doaj.org/toc/2215-0161

Access URL: https://doaj.org/article/5286ad309eb3460d901086c120afb62a

Enhancing a Convolutional Autoencoder with a Quantum Approximate Optimization Algorithm for Image Noise Reduction

Authors: Kit, Tara Pov, Kimsay Kea, Kimleang et al.

Subject Terms: Quantum Physics

Relation: http://arxiv.org/abs/2401.06367

Availability: http://arxiv.org/abs/2401.06367

Comparative Analysis of Quantum and Classical Convolutional Autoencoders on the MNIST Dataset ; Komparativ analys av kvantiska och klassiska konvolutionerande autokodare på MNIST datasetet

Authors: Astorga Castillo, Dante Friman, Lukas

Subject Terms: Quantum computing, Quantum neural network, Quantum machine learning, Convolutional autoencoder, Quantum convolutional autoencoder, Quanvolution, Quanvolutional autoencoder, Kvantberäkning, Kvantneurala nätverk, Kvantmaskininlärning, Konvolutionerande autokodare, Kvantkonvolutionerande autokodare, Computer and Information Sciences, Data- och informationsvetenskap

File Description: application/pdf

Relation: TRITA-EECS-EX; 2024:389

Availability: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-351190

Machine learning enhanced evaluation of semiconductor quantum dots

Authors: Emilio Corcione Fabian Jakob Lukas Wagner et al.

Source: Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)

Subject Terms: Quantum technology, Semiconductor quantum dot, Single photon source, Machine-learning-based evaluation, Convolutional autoencoder, Neural network regression, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/de516114492d4a43929e441ae9c5cca7

Classical-quantum approach to image classification: Autoencoders and quantum SVMs.

Authors: Slabbert, Donovan Petruccione, Francesco

Source: AVS Quantum Science; Jun2025, Vol. 7 Issue 2, p1-15, 15p

Subject Terms: IMAGE recognition (Computer vision), SUPPORT vector machines, AUTOENCODERS, MACHINE learning, IMAGE reconstruction

A Novel Quantum Convolution Neural Network for Image Classification Applications.

Authors: Venkatappa, Venkatachalapathy Madhavanna Venkateshappa

Source: Engineering, Technology & Applied Science Research; Oct2025, Vol. 15 Issue 5, p27046-27051, 6p

Subject Terms: QUANTUM computing, DEEP learning, IMAGE recognition (Computer vision), FEATURE extraction, QUANTUM computers

QHF-CS: Quantum-Enhanced Heart Failure Prediction Using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data.

Authors: Kottapalle, Prasanna Tak, Tan Kuan Kshirsagar, Pravin Ramdas et al.

Source: Computers, Materials & Continua; 2025, Vol. 84 Issue 2, p3857-3892, 36p

Subject Terms: CONVOLUTIONAL neural networks, PARTICLE swarm optimization, HEART failure, MACHINE learning, PSYCHOSOCIAL factors, SUPPORT vector machines

Quantum Classical Algorithm for the Study of Phase Transitions in the Hubbard Model via Dynamical Mean-Field Theory.

Authors: Baul, Anshumitra Fotso, Herbert Terletska, Hanna et al.

Source: Quantum Reports; Jun2025, Vol. 7 Issue 2, p18-N.PAG, 25p

Subject Terms: CONVOLUTIONAL neural networks, QUANTUM phase transitions, MEAN field theory, METAL-insulator transitions, HUBBARD model, QUANTUM computers

Akciğer Röntgen Görüntülerinden Covid-19 ve Zatürre Hastalığının Kuantum Evrişimli Sinir Ağları Yöntemi ile Tahmini. (Turkish)

Alternate Title: Prediction of Covid-19 and Pneumonia Diseases from Lung X-ray Images Using Quantum Convolutional Neural Networks. (English)

Authors: Şahin, Seçmen Harman, Güneş

Source: Karaelmas Science & Engineering Journal / Karaelmas Fen ve Mühendislik Dergisi; tem2024, Vol. 14 Issue 2, p37-51, 15p

Subject Terms: CONVOLUTIONAL neural networks, VIRAL pneumonia, QUANTUM computing, QUANTUM computers, QUBITS, X-ray imaging, LUNGS

Quantum Convolutional Long Short-Term Memory Based on Variational Quantum Algorithms in the Era of NISQ.

Authors: Xu, Zeyu Yu, Wenbin Zhang, Chengjun et al.

Source: Information; Apr2024, Vol. 15 Issue 4, p175, 12p

Subject Terms: CIRCUIT complexity, CONVOLUTIONAL neural networks, QUANTUM states, QUANTUM computing, ALGORITHMS

Uncovering quantum many-body scars with quantum machine learning.

Authors: Feng, Jia-Jin Zhang, Bingzhi Yang, Zhi-Cheng et al.

Source: NPJ Quantum Information; 3/11/2025, Vol. 11 Issue 1, p1-11, 11p

Subject Terms: CONVOLUTIONAL neural networks, QUANTUM states, MACHINE learning, SCARS, QUASIPARTICLES

QUANTUM CONVOLUTIONAL NEURAL NETWORK CIRCUIT

Enhanced ammonia contamination prediction in aquaculture ponds using stereoscopic scalable quantum convolutional networks with simplicial attention network.

Authors: Patil, Mahadev Kalyanrao Kothari, Pritam Pravin Sakamudi, Srilakshmi ramya et al.

Source: Iran Journal of Computer Science; Dec2025, Vol. 8 Issue 4, p2709-2731, 23p