Search Results - Quantum convolutional autoencoder

Optimal satellite selection using quantum convolutional autoencoder for low-cost GNSS receiver applications by Arasavali, Nalineekumari, Kumar, Mogadala Vinod, Gottapu, Sasibhushana Rao, Kumar, Om Prakash, Kakade, Priyanka Desai, Vincent, Shweta, Mane, Pallavi R., Kumar, Sachin

“… This work proposes the quantum convolutional autoencoder-based optimal satellite selection method…”
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QCAE-QOC-SVM: A hybrid quantum machine learning model for DoS and Fuzzy attack detection on autonomous vehicle CAN bus by R, Meghana, Ramesha, Sowmyashree Sakrepatna, Mukhopadhyay, Adwitiya

“… Our approach is a combination of a Quantum Convolutional Autoencoder (QCAE) and a Quantum Orthogonal Classifier based on Support Vector Machines (QOC-SVM…”
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Enhancing a convolutional autoencoder with a quantum approximate optimization algorithm for image noise reduction by Kit, Tara, Pov, Kimsay, Kea, Kimleang, Chang, Won-Du, Chul Park, Hee, Han, Youngsun

“… Owing to their promising efficiency, quantum computers have gained popularity. This paper proposes a method, the quantum convolutional autoencoder (QCAE…”
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INTERNATIONAL PATENT: TELEFONAKTIEBOLAGET LM ERICSSON (PUBL) FILES APPLICATION FOR "A QUANTUM CONVOLUTIONAL AUTOENCODER"

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A Hybrid Quantum enabled RBM Advantage: Convolutional Autoencoders For Quantum Image Compression and Generative Learning by Sleeman, Jennifer, Dorband, John, Halem, Milton

“… We describe a hybrid system that combines a classical deep neural network autoencoder with a quantum annealing Restricted Boltzmann Machine (RBM) using the D-Wave…”
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Enhancing a Convolutional Autoencoder with a Quantum Approximate Optimization Algorithm for Image Noise Reduction by Kea, Kimleang, Won-Du, Chang, Park, Hee Chul, Han, Youngsun

“… Owing to their promising efficiency, quantum computers have gained popularity. This study introduces a quantum convolutional autoencoder (QCAE…”
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Ensemble quantum deep learning for segmentation and classification of central nervous system demyelinating diseases by Satyanarayana, T.V.V., Aravinda Babu, Tummala, Vardhana Reddy, Karna Vishnu, Venkat Reddy, D., Nageswara Rao, M.V.

“…) for joint segmentation and feature extraction, and a hybrid Quantum Autoencoder–Quantum Convolutional Variational (QA–QCV…”
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Quantum-Enhanced Representation Learning: A Quanvolutional Autoencoder Approach against DDoS Threats by Rivas, Pablo, Orduz, Javier, Jui, Tonni Das, DeCusatis, Casimer, Khanal, Bikram

“… Specifically, the quanvolutional autoencoder employs randomized quantum circuits to analyze time-series data from DDoS attacks, offering a robust alternative to classical convolutional neural networks…”
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Machine learning approach to reconstruct density matrices from quantum marginals by Uzcategui-Contreras, Daniel, Guerra, Antonio, Niklitschek, Sebastian, Delgado, Aldo

“…: reconstructing a global density matrix compatible with a given set of quantum marginals. Our method integrates a quantum marginal imposition technique with convolutional denoising autoencoders…”
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Application of image recognition algorithm based on quantum convolutional neural network by Zhao, Xueyang

“… The algorithm combines the advantages of quantum convolutional neural networks (QCNN), autoencoders (AE) and low-lot gradient descent…”
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Denoising gravitational-wave signals from binary black holes with a dilated convolutional autoencoder by Bacon, Philippe, Trovato, Agata, Bejger, Michał

“… The denoising convolutional autoencoder neural network is trained on a dataset of simulated astrophysical signals injected into the real…”
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Semi-supervised underwater acoustic source localization based on residual convolutional autoencoder by Jin, Pian, Wang, Biao, Li, Lebo, Chao, Peng, Xie, Fangtong

“…Passive localization of underwater targets was a thorny problem in underwater acoustics. For traditional model-driven passive localization methods, the main…”
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Towards Quantum Image Generation on Single Qubit using Quantum Information Bottleneck by Zhu, Yijie, Aggarwal, Vaneet, Konar, Debanjan, Pashkin, Yuri, Angelov, Plamen, Jiang, Richard

“…: Quantum Convolutional Variational Autoencoders (QCVAE), designed to operate with only a single qubit…”
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Performance of a convolutional autoencoder designed to remove electronic noise from p-type point contact germanium detector signals by Anderson, Mark R., Basu, Vasundhara, Martin, Ryan D., Reed, Charlotte Z., Rowe, Noah J., Shafiee, Mehdi, Ye, Tianai

“…We present a convolutional autoencoder to denoise pulses from a p-type point contact high-purity germanium detector similar to those used in several rare event searches…”
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CAD-Skin: A Hybrid Convolutional Neural Network–Autoencoder Framework for Precise Detection and Classification of Skin Lesions and Cancer by Khan, Abdullah, Sajid, Muhammad Zaheer, Khan, Nauman Ali, Youssef, Ayman, Abbas, Qaisar

“… This work proposes a novel deep learning algorithm to detect skin cancer. The proposed CAD-Skin system detects and classifies skin lesions using deep convolutional…”
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Anomaly detection by using a combination of generative adversarial networks and convolutional autoencoders by Luo, Xukang, Jiang, Ying, Wang, Enqiang, Men, Xinlei

“…With the development of full digitalization, the amount of time series data generated by sensors is ever-increasing; thus, time series outlier detection has…”
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Feature extraction and classification of heart sound using 1D convolutional neural networks by Li, Fen, Liu, Ming, Zhao, Yuejin, Kong, Lingqin, Dong, Liquan, Liu, Xiaohua, Hui, Mei

“…We proposed a one-dimensional convolutional neural network (CNN) model, which divides heart sound signals into normal and abnormal directly independent of ECG…”
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Lorentz group equivariant autoencoders by Hao, Zichun, Kansal, Raghav, Duarte, Javier, Chernyavskaya, Nadezda

“… To that end, we develop the Lorentz group autoencoder (LGAE), an autoencoder model equivariant with respect to the proper, orthochronous Lorentz group SO + ( 3 , 1…”
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Multi source heterogeneous data diagnosis method of rotating machinery based on parameter collaborative optimization of multi-scale convolutional autoencoder by Yang, Xiaoli

“… data diagnosis method based on parameter collaborative optimization multi-scale convolutional autoencoder (MSCAE) is proposed…”
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Convolutional Machine Learning Method for Accelerating Nonequilibrium Green's Function Simulations in Nanosheet Transistor by Aleksandrov, Preslav, Rezaei, Ali, Dutta, Tapas, Xeni, Nikolas, Asenov, Asen, Georgiev, Vihar

“… The device simulations are based on the quantum mechanical nonequilibrium Green's function (NEGF…”
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