Deep Learning for Computer Vision Application

Dear Colleagues,

Artificial intelligence (AI) methods, and more specifically deep neural networks (also called deep learning models), have became the core technique for computer vision tasks across various applications. The advent of these powerful deep learning models allows state-of-the-art automation levels in autonomous pattern recognition from image data. In a general sense, the ultimate manifestation of these techniques can be seen in our daily life, from automatically sorting and retrieving photos in Google photos to autonomous cars. However, these powerful techniques still have not been utilized in all computer vision tasks. Future studies should seek to find more applications of AI in our life, e.g., via data acquisition and cleaning, as well as more model optimization, innovation, and research. In this Special Issue, we are particularly interested in new applications of deep learning in the computer vision field.

Topics of interest include but are not limited to:

• Image classification using deep learning;
• Object detection using deep learning;
• Semantic and instant segmentation using deep learning;
• Deep learning techniques for generating new images (generative adversarial networks);
• Employing reinforcement learning for computer vision tasks;
• Application of deep learning in the Internet of Things (IoT);
• Application of deep learning in embedded systems, sensor development, and electronics;
• Computer vision tasks using deep learning (medical image processing, remote sensing, hyperspectral imaging, thermal imaging, space and extraterrestrial observations);
• Image sequence analysis using deep learning;
• Deep learning and computer vision for smart and green building, smart industry, and smart devices.

Dr. Hamed Mozaffari
Guest Editor

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