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Objects in unmanned aerial vehicle (UAV) images are generally small due to the high-photography altitude. Although many efforts have been made in object detection, how to accurately and quickly detect small objects is still one of the remaining open challenges. In this paper, we propose a feature fusion and scaling-based single shot detector (FS-SSD) for small object detection in the UAV images. The FS-SSD is an enhancement based on FSSD, a variety of the original single shot multibox detector (SSD). We add an extra scaling branch of the deconvolution module with an average pooling operation to form a feature pyramid. The original feature fusion branch is adjusted to be better suited to the small object detection task. The two feature pyramids generated by the deconvolution module and feature fusion module are utilized to make predictions together. In addition to the deep features learned by the FS-SSD, to further improve the detection accuracy, spatial context analysis is proposed to incorporate the object spatial relationships into object redetection. The interclass and intraclass distances between different object instances are computed as a spatial context, which proves effective for multiclass small object detection. Six experiments are conducted on the PASCAL VOC dataset and the two UAV image datasets. The experimental results demonstrate that the proposed method can achieve a comparable detection speed but an accuracy superior to those of the six state-of-the-art methods. [ABSTRACT FROM AUTHOR]

A compact solid-state UV flame sensing system is developed and tested. We have addressed two approaches for obtaining additional six orders of long-wavelength rejection power on top of that of the built-in UV sensor based on a wide-bandgap II–VI Schottky-barrier structure. An op-amp-based amplification circuit with an average gain of 16 600 is used for signal amplification. It is demonstrated that the developed sensing system could detect a standard butane-air flame with excellent solar-blind characteristics, potentially capable for monitoring industrial boilers. Several feasible approaches were discussed for further improvement in the performance of the developed sensing system targeting its general usage in fire-safety applications. [ABSTRACT FROM PUBLISHER]