SSD-TSEFFM: New SSD Using Trident Feature and Squeeze and Extraction Feature Fusion.

The single shot multi-box detector (SSD) exhibits low accuracy in small-object detection; this is because it does not consider the scale contextual information between its layers, and the shallow layers lack adequate semantic information. To improve the accuracy of the original SSD, this paper proposes a new single shot multi-box detector using trident feature and squeeze and extraction feature fusion (SSD-TSEFFM); this detector employs the trident network and the squeeze and excitation feature fusion module. Furthermore, a trident feature module (TFM) is developed, inspired by the trident network, to consider the scale contextual information.

Optimal parameter retrieval for metamaterial absorbers using the least-square method for wide incidence angle insensitivity.

In this paper, we propose a specific algorithm based on the least-square method to predict the incidence angle insensitivity of a metamaterial absorber. The proposed algorithm was analyzed on a metamaterial absorber design with circular sectors on the top layer and a full copper cover on the bottom layer. We retrieved the parameters of inductance, capacitance, and conductance from the equivalent circuit of the metamaterial absorber at different incidence angles of 0°, 30°, 65°, and 70° under both transverse electric and transverse magnetic polarization.