The specklegram analysis due to macro-bending of optical fibers has been widely employed for different sensing purposes. In this work, we mainly detect the random, multiple macro-bending loss by employing a deep learning-based convolutional neural network (CNN) namely the AlexNet model. Here, we detect the discrete losses corresponding to six macro-bends of different radii at six different locations of plastic optical fiber (POF). The proposed model can detect the macro-bending losses with 100% detection accuracy which signifies the efficacy of the proposed AlexNet model. In perspective, our results may pave the way for developing a deep-learning methodology for the smart detection of several, discrete macro-bending losses in POFs for several sensing applications.
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