Image Sensing Detection in Bio-Systems Using Convolutional Neural Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 5392
Special Issue Editors
Interests: signal and image processing; optimization; biomedical image analysis; deep learning; robotics in agriculture
Interests: machine learning; image analysis; computer vision
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Introduction: Deep learning is fast emerging as the state-of-the-art approach in many problems in image analysis and computer vision across several scientific domains in the life sciences, including biomedical image analysis and computer vision in agriculture. This Special Issue is focused on solving computer vision problems in bio-systems (e.g., digital phenotyping, agricultural yield estimation, disease detection, and wildlife monitoring) by using convolutional neural networks for object detection. As the field of deep learning is driven by data, the use of these techniques requires area-specific insights. We invite high-quality, previously unpublished contributions on any topics related to the use of deep learning object detection in the aforementioned areas, including (but not limited to) the following:
- Novel algorithms and convolutional neural network architectures;
- Innovative use cases in the life sciences;
- Sensor fusion and multimodality image analysis;
- Datasets, including synthetic datasets and transfer learning.
Dr. Manya Afonso
Dr. Catarina Barata
Dr. Carlos Santiago
Guest Editors
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Keywords
- deep learning
- convolutional neural networks
- object detection
- bio-systems
- biomedical image analysis
- computer vision in life science
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