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Deep convolutional neural networks (CNNs) have revolutionized the computer vision research and have seen unprecedented adoption for multiple tasks, such as classification, detection, and caption generation. However, they offer little transparency into their inner workings and are often treated as black boxes that deliver excellent performance.
Defocus blur detection is an important and challenging task in computer vision and digital imaging fields. Previous work on defocus blur detection has put a lot of effort into designing local sharpness metric maps.
With the advent of ubiquitous sensing and real-time data processing, the demand for engineers with solid signal processing skills has exceeded the supply by a large margin. However, even students in technical subjects often perceive signal processing as demanding and somewhat dry [4].
Each "Reader’s Choice" column focuses on a different publication of the IEEE Signal Processing Society. This month we are highlighting articles in IEEE Transactions on Signal and Information Processing over Networks (T-SIPN).
Functions of complex variables arise frequently in the formulation of sig - nal processing problems. The basic calculus rules on differentiation and integration for functions of complex variables resemble, but are not identical to, the rules of their real variable counterparts.
Industrial control systems (ICSs) manage and monitor critical civil or military infrastructure, such as water treatment facilities, power plants, electricity grids, transportation systems, oil and gas refineries, and health care.
In this column of IEEE Signal Processing Magazine, 46 IEEE Signal Processing Society (SPS) members are recognized as IEEE Fellows and award recipients are announced.