Special Issue "Deep Learning for Nondestructive Detection and Analysis Using Hyperspectral Imaging"
Deadline for manuscript submissions: 20 April 2023 | Viewed by 1634
Interests: hyperspectral imaging; artificial intelligence; deep learning; real-time machine vision; non-destructive sensing of agricultural and food products for safety and quality assessment; big image data
Special Issues, Collections and Topics in MDPI journals
Special Issue in Applied Sciences: Advanced Optical Imaging and Sensing Techniques for Smart Farming and Food Processing
Special Issue in Foods: Nondestructive Optical Sensing for Food Quality and Safety Inspection
Special Issue in Agriculture: Sensors Applied to Agricultural Products
In recent years, deep learning has shown tremendous performance and promise in various visual information extraction, detection, and analysis tasks for diverse scientific communities and industries. Hyperspectral images carry both visual and spectral information, which has proven to be really useful and effective for nondestructive visual detection and analysis tasks. With the advent of deep learning, a lot of progress has been made in deep learning-based hyperspectral image processing and analysis, especially for remote sensing applications. Still, a lot of work needs to be done for many other applications to improve deep learning-based hyperspectral imaging and find solutions to challenging real-world problems. This Special Issue aims to introduce and promote recent research on adaptation and applications of deep learning for hyperspectral image processing and analysis. This Special Issue is particularly interested in recent work involving new and innovative methods for nondestructive quality and safety assessment and sensing of materials and products with deep learning-based hyperspectral imaging.
We solicit both original research papers and review articles on various aspects of deep learning-based hyperspectral imaging, including but not limited to, the following topics and applications:
- Transfer learning
- Deep learning architectures and models
- Quality and safety assessment of agriculture and food products
- Plant phenotyping
- Environment monitoring
- Precision agriculture
- Health and medical applications
- Sensor/data fusion
- Spectral image management, pretreatment, and processing
Dr. Seung-Chul Yoon
Manuscript Submission Information
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