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LPMP: A Bio-Inspired Model for Visual Localization in Challenging Environments

Sylvain Colomer, Sylvain Colomer, Nicolas Cuperlier, Guillaume Bresson et al. • Frontiers in Robotics and AI (2022)

Autonomous vehicles require precise and reliable self-localization to cope with dynamic environments. The field of visual place recognition (VPR) aims to solve this challenge by relying on the visual modality to recognize a place despite ch...

DOAJ Open Access (DOAJ) DOI: 10.3389/frobt.2021.703811

Disaster Robotics

Robin Roberson Murphy • The MIT Press eBooks (2014)

A comprehensive, authoritative, and accessible reference for disaster robotics that covers theory, specific deployments, and ground, air, and marine modalities. This book offers the definitive guide to the theory and practice of disaster ro...

OPENALEX DOI: https://doi.org/10.7551/mitpress/9407.001.0001

Multimodal deep learning for automated atomic qubits fabrication in silicon

Yuwei Cui, Kunrong Wu, Ping Wu, Luyan Yang et al. • Machine Learning: Science and Technology (2026)

Donor-based spin qubits in silicon are a promising platform for scalable quantum computing due to their long coherence times and high-fidelity gate operations. A viable path for fabricating donor qubit arrays with atomic precision is scanni...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/ae8e30

Sensitivity and Features of Computed Tomography in Diagnosis of COVID-19 Pneumonia: A Meta-analysis

Awadia Gareeballah, Moawia Gameraddin, Sultan Abdulwadoud Alshoabi, Lubna Bushara et al. • Journal of Clinical and Diagnostic Research (2021)

Introduction: Early diagnosis of COVID-19 is important for disease treatment and management. Computed Tomography (CT) is a fast and easy modality for diagnosis and management plan of patients with COVID-19. In the literature, several stu...

DOAJ Open Access (DOAJ) DOI: 10.7860/JCDR/2021/47449.14570

QG-WRN: A Quantum-Enhanced Graph Convolutional Wide Residual Network for ASD Diagnosis via Neuroimaging Sensing Technology

Nanting Huang, Xiaoyu Li, Xin Yang, Li Xie et al. • Sensors (2026)

The pathological mechanism of autism spectrum disorder (ASD) exhibits dual heterogeneity: abnormal local energy metabolism and brain-wide high-order topological failure. To synergistically characterize these complex signals captured by adva...

DOAJ Open Access (DOAJ) DOI: 10.3390/s26133997

Multimodal Phase-Space Dynamics Fusion for Robust Ischemia Screening: An Edge-AI Paradigm with SERF Magnetocardiography

Keyi Li, Xiangyang Zhou, Yifan Jia, Ruizhe Wang et al. • Biosensors (2026)

Background: Myocardial ischemia (MI) is a major cause of morbidity and mortality worldwide and requires timely and reliable detection. Although Spin-Exchange Relaxation-Free (SERF) magnetocardiography (MCG) provides femtotesla-level sensiti...

DOAJ Open Access (DOAJ) DOI: 10.3390/bios16040228

Multimodal Deep Learning

Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam et al. (2011)

Deep networks have been successfully applied to unsupervised feature learning for single modalities (e.g., text, images or audio). In this work, we propose a novel application of deep networks to learn features over multiple modalities. We ...

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An overview of deep learning in the field of dentistry

Jae Joon Hwang, Yun‐Hoa Jung, Bong‐Hae Cho, Min-Suk Heo • Imaging Science in Dentistry (2019)

PURPOSE: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about d...

OPENALEX cc-by-nc DOI: https://doi.org/10.5624/isd.2019.49.1.1 PMC: 6444007

Deep Learning for Health Informatics

Daniele Ravì, Charence Wong, Fani Deligianni, Melissa Berthelot et al. • IEEE Journal of Biomedical and Health Informatics (2016)

With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on mac...

OPENALEX cc-by DOI: https://doi.org/10.1109/jbhi.2016.2636665