arXiv Machine Learning By Claudia Corradino, Federica Torrisi, Alessandro Grilli, Tommaso Catuogno, Mattia Verducci, Elisabetta Paladino, Luigi Giannelli, Alessandro Sebastianelli

Hybrid Quantum CNN for Cross-Sensor Spaceborne Volcanic Thermal Activity Recognition Worldwide

Read the original on arXiv Machine Learning →

arXiv:2608. 00069v1 Announce Type: cross Abstract: As Earth Observation (EO) enters the Big Data era, the exponential volume of daily satellite imagery poses significant computational and storage challenges for classical Deep Learning (DL) models.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Jul 17

QFireNet: A Quantum-Enhanced U-Net for Wildfire Segmentation from Sentinel-2 Imagery

arXiv:2607. 14160v1 Announce Type: new Abstract: Wildfire detection from satellite imagery is a semantic image segmentation problem that has proven to be difficult due to challenges such as class imbalance, feature complexity, and atmospheric interference.

By Jaiman Munshi (IonQ Team, App Dev Club, University of Maryland, College Park), Tanvi Tewary (IonQ Team, App Dev Club, University of Maryland, College Park), Sawyer Bloom (IonQ Team, App Dev Club, University of Maryland, College Park), Aidan Chu (IonQ Team, App Dev Club, University of Maryland, College Park), Chetan Maviti (IonQ Team, App Dev Club, University of Maryland, College Park), Kyon Winston-Bey (IonQ Team, App Dev Club, University of Maryland, College Park), Harshit Badjatia (IonQ Team, App Dev Club, University of Maryland, College Park), Farhan Kittur (IonQ Team, App Dev Club, University of Maryland, College Park), Vardhan Madhavarapu (IonQ Team, App Dev Club, University of Maryland, College Park), Varun Kota (IonQ Team, App Dev Club, University of Maryland, College Park), Joshua Kwon (IonQ Team, App Dev Club, University of Maryland, College Park), Nazia Rangwala-Vohra (IonQ Team, App Dev Club, University of Maryland, College Park), Franz Klein (IonQ Team, App Dev Club, University of Maryland, College Park)
arXiv Machine Learning
Jul 27

Parameterized Quantum Circuits as Feature Maps: Representation Quality and Readout Effects in Multispectral Land-Cover Classification

arXiv:2604. 26675v2 Announce Type: replace-cross Abstract: We investigate variational quantum classifiers (VQCs) for land-cover classification from multispectral satellite imagery, adopting a feature-map perspective in which the quantum circuit defines a nonlinear data embedding while the readout determines how this representation is exploited.

By Ralntion Komini, Aikaterini Mandilara, Georgios Maragkopoulos, Dimitris Syvridis
arXiv Machine Learning
Jun 26

Tailor Made Embeddings for Quantum Machine Learning

arXiv:2606. 26312v1 Announce Type: cross Abstract: Autoencoders transformed classical machine learning by solving the curse of dimensionality, enabling principled weight initialization and learning compact, structured representations.

By Aldo Lamarre, Dominik \v{S}afr\'anek
arXiv AI
Jul 9

QCNN with Rough Path Signature Kernels

arXiv:2607. 07634v1 Announce Type: cross Abstract: Time series analysis plays a vital role across a wide range of scientific and engineering domains but poses substantial computational challenges.

By Leonardo Nogueira Falabella, Vasily Sazonov
arXiv Machine Learning
Jul 27

Do emulated quantum circuits change what CNNs look at? Performance and explainability comparison in medical image classification

arXiv:2607. 21186v1 Announce Type: cross Abstract: Numerous studies have analyzed the use of hybrid quantum-classical convolutional neural networks as a promising alternative to classical deep learning.

By Guillermo Rubi\~nos Rodr\'iguez, Mart\'in Ottavianelli, Mateo Alonso, Gonzalo Bl\'azquez Gil, Boris-Stephan Rauchmann, Pablo D\'iez-Valle, Sergio Altares-L\'opez