Intelligent Recognition and Detection for Unmanned Systems

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Bol The present reprint contains the 12 articles accepted and published in a Special Issue of the MDPI journal Drones entitled "Intelligent Recognition and Detection for Unmanned Systems, 2023"; this Special Issue covers a wide range of topics connected to the theory and application of AI algorithms in intelligent recognition and detection for unmanned systems. These keywords include object recognition (i.e., image recognition and speech recognition), object detection, flexible CNNs, deep learning, NLP, drone, smart robot, etc. Unmanned systems (i.e., droned, robots and other intelligent systems) play an important role in many fields, i.e., disaster relief, intelligent transportation, intelligent medical service and space exploration. Furthermore, object recognition and detection have been employed extensively in these tasks. However, due to complex application environments, artificial intelligence techniques suffer from challenges in terms of robustness and flexibility. Thus, designing efficient and stable CNNs and other AI algorithms for object recognition and detection in unmanned systems is critical. It is hoped that this reprint will provide insights for those working in the area of computer vision, artificial intelligence and unmanned systems, as well as those with the proper scientific background and willing to familiarize themselves with recent advances in unmanned systems.

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The present reprint contains the 12 articles accepted and published in a Special Issue of the MDPI journal Drones entitled "Intelligent Recognition and Detection for Unmanned Systems, 2023"; this Special Issue covers a wide range of topics connected to the theory and application of AI algorithms in intelligent recognition and detection for unmanned systems. These keywords include object recognition (i.e., image recognition and speech recognition), object detection, flexible CNNs, deep learning, NLP, drone, smart robot, etc. Unmanned systems (i.e., droned, robots and other intelligent systems) play an important role in many fields, i.e., disaster relief, intelligent transportation, intelligent medical service and space exploration. Furthermore, object recognition and detection have been employed extensively in these tasks. However, due to complex application environments, artificial intelligence techniques suffer from challenges in terms of robustness and flexibility. Thus, designing efficient and stable CNNs and other AI algorithms for object recognition and detection in unmanned systems is critical. It is hoped that this reprint will provide insights for those working in the area of computer vision, artificial intelligence and unmanned systems, as well as those with the proper scientific background and willing to familiarize themselves with recent advances in unmanned systems.


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