Advanced Deep Learning Techniques for Intelligent Sensor Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (28 February 2026) | Viewed by 965
Special Issue Editors
Interests: large model (LLM, LMM, VLM, LAM, etc.)
Special Issues, Collections and Topics in MDPI journals
Interests: agentic AI; multi-agent systems; reasoning models
Special Issue Information
Dear Colleagues,
Recently, the diverse kinds of advanced deep learning techniques are developed depending on sensor configuration and goals of applications in robotics, autonomous driving, smart factoring, healthcare, and so on. Given that massive sensor data are collected and processed as learning data, deep learning models become more complicated and are integrated. Therefore, this Special Issue aims to implement advanced models and frameworks of deep learning for intelligent sensor systems.
Potential topics include, but are not limited to, the following:
- Deep learning-based sensor simulation;
- Deep learning-driven control loops with sensor feedback;
- Natural language interface for sensor querying;
- Sensor data fusion with large multimodal models;
- Human–AI interaction (HAI);
- Human–Agent collaboration for sensor monitoring and data analysis;
- Multi-agent system for sensor monitoring and data analysis;
- Potential biases of agentic AI in decision making with sensors;
- Anomaly detection in sensor setworks Using LLMs;
- Sensor simulation with deep learning or generative LLMs;
- Potential hallucination of LLM/LLM-based sensor analysis;
- Instruction tuning methods/datasets for constructing large sensor-language models;
- Reasoning models for sensor data analysis/querying;
- Application of large sensor-language models.
Dr. Yunsick Sung
Dr. Bugeun Kim
Guest Editors
Manuscript Submission Information
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Keywords
- deep learning
- large language mode
- large multimodal model
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