Object detection has been a building block in computer vision. Though considerable progress has been made, there still exist challenges for objects with small size, arbitrary direction, and dense distribution. Apart from natural images, such issues are especially pronounced for aerial images of great importance. This paper presents a novel multicategory rotation detector for small, cluttered and rotated objects, namely SCRDet. Specifically, a sampling fusion network is devised which fuses multi-layer feature with effective anchor sampling, to improve the sensitivity to small objects. Meanwhile, the supervised pixel attention network and the channel attention network are jointly explored for small and cluttered object detection by suppressing the noise and highlighting the objects feature. For more accurate rotation estimation, the IoU constant factor is added to the smooth L1 loss to address the boundary problem for the rotating bounding box. Extensive experiments on two remote sensing public datasets DOTA, NWPU VHR-10 as well as natural image datasets COCO, VOC2007 and scene text data ICDAR2015 show the state-of-the-art performance of our detector. The code and models will be available at https://github.com/DetectionTeamUCAS.

Ship detection has been playing a significant role in the field of remote sensing for a long time, but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection, and the redundancy of the detection region. In order to solve these problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ships in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving problems resulting from the narrow width of the ship. Compared with previous multiscale detectors such as Feature Pyramid Network (FPN), DFPN builds high-level semantic feature-maps for all scales by means of dense connections, through which feature propagation is enhanced and feature reuse is encouraged. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multiscale region of interest (ROI) Align for the purpose of maintaining the completeness of the semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has state-of-the-art performance.

Biotransformation is a critical factor that may modify the toxicity, behavior, and fate of engineered nanoparticles in the environment. CeO2 nanoparticles (NPs) are generally recognized as stable under environmental and biological conditions. The present study aims to investigate the biotransformation of CeO2 NPs in plant systems. Transmission electron microscopy (TEM) images show needlelike clusters on the epidermis and in the intercellular spaces of cucumber roots after a treatment with 2000 mg/L CeO2 NPs for 21 days. By using a soft X-ray scanning transmission microscopy (STXM) technique, the needlelike clusters were verified to be CePO4. Near edge X-ray absorption fine structure (XANES) spectra show that Ce presented in the roots as CeO2 and CePO4 while in the shoots as CeO2 and cerium carboxylates. Simulated studies indicate that reducing substances (e.g., ascorbic acids) played a key role in the transformation process and organic acids (e.g., citric acids) can promote particle dissolution. We speculate that CeO2 NPs were first absorbed on the root surfaces and partially dissolved with the assistance of the organic acids and reducing substances excreted by the roots. The released Ce(III) ions were precipitated on the root surfaces and in intercellular spaces with phosphate, or form complexes with carboxyl compounds during translocation to the shoots. To the best of our knowledge, this is the first report confirming the biotransformation and in-depth exploring the translocation process of CeO2 NPs in plants.