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Deep Learning for Understanding Satellite Imagery: An Experimental Survey

Sharada Prasanna Mohanty, Jakub Czakon, Kamil A. Kaczmarek, Kamil A. Kaczmarek et al. • Frontiers in Artificial Intelligence (2020)

Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in compu...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2020.534696

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access (2020)

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3039858

Up-to-Date Scoping Review of Object Detection Methods for Macro Marine Debris

Zoe Moorton, Kamlesh Mistry, Rebecca Strachan, Shanfeng Hu • Journal of Marine Science and Engineering (2025)

Being able to accurately identify litter in a marine environment is crucial to cleaning up our seas and oceans. Research into object detection techniques to support this identification has been underway for over two decades. However, there ...

DOAJ Open Access (DOAJ) DOI: 10.3390/jmse13081590

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

Turning Features Detection from Aerial Images: Model Development and Application on Florida’s Public Roadways

Richard Boadu Antwi, Michael Kimollo, Samuel Yaw Takyi, Eren Erman Ozguven et al. • Smart Cities (2024)

Advancements in computer vision are rapidly revolutionizing the way traffic agencies gather roadway geometry data, leading to significant savings in both time and money. Utilizing aerial and satellite imagery for data collection proves to b...

DOAJ Open Access (DOAJ) DOI: 10.3390/smartcities7030059

Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials

Haijie Ren, Weiqiang Wang, Wentao Tang, Rui Zhang • Physical Review Research (2024)

Topological defects play a key role in the structures and dynamics of liquid crystals and other ordered systems. There is a recent interest in studying defects in different biological systems with distinct textures. However, a robust method...

DOAJ Open Access (DOAJ) DOI: 10.1103/PhysRevResearch.6.013259

Computer vision and machine‐learning techniques for quantification and predictive modeling of intracellular anticancer drug delivery by nanocarriers

Sanjay Goswami, Kshama D. Dhobale, Ravindra D. Wavhale, Barnali Goswami et al. • Applied AI Letters (2022)

Abstract The field of cancer nanomedicine has made significant progress, but its clinical translation is impeded by many challenges, such as the difficulty in analyzing intracellular anticancer drug release by the nanocarriers due to the la...

DOAJ Open Access (DOAJ) DOI: 10.1002/ail2.50

New topic horizons for drone systems and applications

Karen Anderson, Brandi M. Shabaga, Serge Wich, Geoff Fink et al. • Drone Systems and Applications (2023)

Summary This journal (Drone Systems and Applications; DSA) conducted a targeted “horizon scan” during 2022 within our team of editors and associate editors. We asked—Which research areas currently under-represented in Drone Systems and Appl...

DOAJ Open Access (DOAJ) DOI: 10.1139/dsa-2023-0019

Retrieval of carbon dioxide vertical concentration profiles from satellite data using artificial neural networks

A. Roberto Carvalho, F. Manoel Ramos, J. Carlos Carvalho • Trends in Computational and Applied Mathematics (2010)

Abstract. In this paper, we derive vertical distributions of carbon dioxide atmospheric concentration from satellite data using a retrieval algorithm based on an artificial neural network (ANN) technique. Sensitivity studies were made to se...

DOAJ Open Access (DOAJ) DOI: 10.5540/tema.2010.011.03.0205

Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics

F. Cadini, E. Zio, N. Pedroni • Science and Technology of Nuclear Installations (2008)

Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control appli...

DOAJ Open Access (DOAJ) DOI: 10.1155/2008/681890

Dissipativity analysis of stochastic fuzzy neural networks with randomly occurring uncertainties using delay dividing approach

Sundaram Senthilraj, Ramachandran Raja, Jinde Cao, Habib M. Fardoun • Nonlinear Analysis (2019)

This paper focuses on the problem of delay-dependent robust dissipativity analysis for a class of stochastic fuzzy neural networks with time-varying delay. The randomly occurring uncertainties under consideration are assumed to follow certa...

DOAJ Open Access (DOAJ) DOI: 10.15388/NA.2019.4.5

Artificial neural networks in medical diagnosis

Filippo Amato, Alberto Botana López, Eladia María Peña‐Méndez, Petr Vaňhara et al. • Journal of Applied Biomedicine (2013)

An extensive amount of information is currently available to clinical specialists, ranging from details of clinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of data provides information that mu...

OPENALEX Open Access DOI: https://doi.org/10.2478/v10136-012-0031-x

An introduction to neural networks

• Choice Reviews Online (1998)

From the Publisher: An Introduction to Nueral Networks will be warmly welcomed by a wide readership seeking an authoritative treatment of this key subject without an intimidating level of mathematics in the presentation....

OPENALEX DOI: https://doi.org/10.5860/choice.35-5700

Introduction Neural networks in remote sensing

Peter M. Atkinson, Adrian R. L. Tatnall • International Journal of Remote Sensing (1997)

Abstract. Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that ...

OPENALEX DOI: https://doi.org/10.1080/014311697218700

Shear banding and flow instabilities in wormlike micelles: Modelling and mechanisms – A review

Sudheesh Parathakkatt, Vaisakh Kizhuveetil, Gokul G. K., Rajashree Ajay Markandewar • eXPRESS Polymer Letters (2026)

Worm-like micelles (WLMs) are dynamic, self-assembling supramolecular structures that exhibit complex viscoelastic behaviour due to their ability to undergo reversible scission, fusion, branching, and sequence rearrangement. This review pro...

DOAJ Open Access (DOAJ) DOI: 10.3144/expresspolymlett.2026.36