In view of the lack of feature complementarity between the feature layers of Single Shot MultiBox Detector (SSD) and the weak detection ability of SSD for small objects, we propose an improved SSD object detection algorithm based on Dense Convolutional Network (DenseNet) and feature fusion, which is called DF-SSD. On the basis of SSD, we design the feature extraction network DenseNet-S-32-1 with reference to the dense connection of DenseNet, and replace the original backbone network VGG-16 of SSD with DenseNet-S-32-1 to enhance the feature extraction ability of the model. In the part of multi-scale detection, a fusion mechanism of multi-scale feature layers is introduced to organically combine low-level visual features and high-level semantic features in the network structure. Finally, a residual block is established before the object prediction to further improve the model performance. We train the DF-SSD model from scratch. The experimental results show that our model DF-SSD with 300 × 300 input achieves 81.4% mAP, 79.0% mAP, and 29.5% mAP on PASCAL VOC 2007, VOC 2012, and MS COCO datasets, respectively. Compared with SSD, the detection accuracy of DF-SSD on VOC 2007 is improved by 3.1% mAP. DF-SSD requires only 1/2 parameters to SSD and 1/9 parameters to Faster RCNN. We inject more semantic information into DF-SSD, which makes it have advanced detection effect on small objects and objects with specific relationships.INDEX TERMS DenseNet, feature fusion, multi-scale object detection, SSD.

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It has been a challenge to improve the toughness of intermetallic compound at low and medium temperatures for developing wear resistance materials. The refractory metals, with a high melting point, strong atomic bonds, high ductility and toughness, are ideal toughening phases for intermetallic composites. This paper presents a novel composite having the microstructure of ductile Mo primary dendrites, binary intermetallic compound NiMo and ternary metallic silicide Mo 2 Ni 3 Si. The composite exhibits outstanding wear resistance and pretty low wear-load coef cient at ambient temperature, which are attributed to the contribution of refractory metal Mo to toughness of intermetallic matrix, in addition to the high strength and hardness of binary NiMo and ternary Mo 2 Ni 3 Si intermetallic phases. The wear mechanism analyzed by examining the worn surface and debris morphologies is in terms of soft abrasive wear.

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