The intelligentization of future society puts forward an urgent demand for high-precision sensing and ultra-high-speed wireless communications in the upcoming beyond fifth-generation (B5G) era. We …
Dispersive waves (DWs) are ubiquitous in nonlinear optical systems that host optical solitons. In particular, DWs in soliton fiber lasers have attracted continuous interest over the past decades si…
With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable result…
Person re-identification (Re-ID) via gait features within 3D skeleton sequences is a newly-emerging topic with several advantages. Existing solutions either rely on hand-crafted descriptors or supe…
Spectral clustering (SC) has become one of the most widely-adopted clustering algorithms, and been successfully applied into various applications. We in this work explore the problem of spectral cl…
We experimentally utilize a tunable, broadband pixel-array-based integrated receiver for recovering orbital-angular-momentum (OAM) multiplexed channels. The OAM receiver comprises a pixel-array-bas…
We experimentally demonstrate turbulence-resilient free-space optical (FSO) coherent communications with multiple multiplexed data channels in different orthogonal domains, including mode, polariza…
Deep learning methods such as convolutional neural networks (CNN) have been shown to be highly effective in complex nonlinear modeling or classification in multimode fiber transmission systems with…
We have experimentally analyzed and compared the performance of optical frequency domain reflectometry (OFDR) assisted by image processing methods including wavelet transform and Gaussian filter ar…
To build a flexible and interpretable model for document analysis, we develop deep autoencoding topic model (DATM) that uses a hierarchy of gamma distributions to construct its multi-stochastic-lay…