Mou Wang

TL;DR: Experimental results reveal that ship detection and instance segmentation can be well implemented on HRSID, and this work has constructed a High-Resolution SAR Images Dataset (HRSID).

TL;DR: The measured results show that the proposed method has achieved high accuracies of common four kinds of measured radar signals, and has higher average accuracy and better performance under low SNR condition.

TL;DR: A novel compressive sensing (CS)-based imaging and autofocusing framework is proposed to obtain high cross-range resolution for SA ISAR and its corresponding network-based AF-AMPNet is proposed, which show superior performance, robustness, and higher efficiency than other state-of-the-art methods.

TL;DR: A novel 3-D microwave sparse reconstruction method based on a complex-valued sparse reconstruction network (CSR-Net), which converts complex number operations into matrix operations for real and imaginary parts and outperforms both conventional iterative threshold optimization methods and deep network-based ISTA-NET-plus large margins.

TL;DR: Wang et al. as discussed by the authors proposed a two-path iterative framework for 3D SAR sparse imaging by mapping the AMP into a layer-fixed deep neural network, each layer of TPSSI-Net consists of four modules in cascade corresponding to four steps of the Onsager optimization.