Hyperspectral imaging has attracted significant attention to identify spectral signatures for image classification and automated pattern recognition in computer vision. State-of-the-art implementations of snapshot hyperspectral imaging rely on bulky, non-integrated, and expensive optical elements, which do not allow fast data processing, e.g., real-time and high-resolution videos. This work introduces Hyplextm, a CMOS-compatible, fast hyperspectral camera that replaces bulk optics with suitably designed artificial intelligent optical hardware components. Hyplextm does not require spectrometers but uses conventional monochrome cameras, allowing real-time and high-resolution hyperspectral imaging at inexpensive costs. In this invited talk, we discuss the design, implementation, and real-world applications of Hyplextm.
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