Neural Network-Based Approaches for Intelligent Sensing and Data Analysis
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 25 April 2026 | Viewed by 29
Special Issue Editors
Interests: evolutionary design and optimization; evolvable hardware; modelling and optimization of large systems; operational research; robotics; swarm optimization
Special Issues, Collections and Topics in MDPI journals
Interests: Neuromorphic engineering; edge computer vision; bio-inspired computing; robotics and intelligent sensors; retinal cell understanding; biological nervous system modelling; spiking neural networks; robotics and autonomous systems; and neuromorphic hardware; aquaculture; endangered/invasive underwater species
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on the integration of neural network-based techniques in intelligent sensing and data analysis. With the rapid expansion of sensor technologies and the increasing complexity of data, neural networks—especially deep learning models—offer robust solutions for extracting meaningful insights, detecting patterns, and enabling autonomous decision-making.
We welcome contributions that explore novel neural architectures, hybrid models, and practical implementations across various domains, including healthcare, environmental monitoring, smart cities, industrial automation, and IoT. Topics of interest may include, but are not limited to, the following:
- Sensor data fusion using neural networks;
- Deep learning for time-series and spatial data;
- Edge AI for real-time sensing and analysis;
- Explainable neural models in sensor systems;
- Event detection and anomaly recognition;
- Applications in robotics, biomedical sensing, and autonomous systems.
This Special Issue aims to bring together interdisciplinary research that advances the capabilities of intelligent sensing systems through neural network innovations, fostering collaboration between academia and industry.
Prof. Dr. Tatiana Kalganova
Dr. Pedro Machado
Guest Editors
Manuscript Submission Information
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Keywords
- sensor data fusion
- neural networks
- AI for real-time sensing
- intelligent sensing
- anomaly recognition
- deep learning for time-series and spatial data
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