Zobrazeno 1 - 10
of 465
pro vyhledávání: '"Zheng Siming"'
Deep learning has revolutionized the process of new material discovery, with state-of-the-art models now able to predict material properties based solely on chemical compositions, thus eliminating the necessity for material structures. However, this
Externí odkaz:
http://arxiv.org/abs/2309.04482
Autor:
Zheng, Siming, Yuan, Xin
We consider the problem of video snapshot compressive imaging (SCI), where sequential high-speed frames are modulated by different masks and captured by a single measurement. The underlying principle of reconstructing multi-frame images from only one
Externí odkaz:
http://arxiv.org/abs/2306.11316
We propose a mutual information-based sufficient representation learning (MSRL) approach, which uses the variational formulation of the mutual information and leverages the approximation power of deep neural networks. MSRL learns a sufficient represe
Externí odkaz:
http://arxiv.org/abs/2207.10772
Autor:
Zheng, Siming, Xue, Yujia, Tahir, Waleed, Wang, Zhengjue, Zhang, Hao, Meng, Ziyi, Qu, Gang, Ma, Siwei, Yuan, Xin
We consider the image and video compression on resource limited platforms. An ultra low-cost image encoder, named Block Modulating Video Compression (BMVC) with an encoding complexity ${\cal O}(1)$ is proposed to be implemented on mobile platforms wi
Externí odkaz:
http://arxiv.org/abs/2205.03677
Publikováno v:
In Renewable Energy December 2024 237 Part A
Publikováno v:
In Applied Ocean Research November 2024 152
Publikováno v:
In Engineering Applications of Artificial Intelligence October 2024 136 Part A
Publikováno v:
In Information Sciences January 2025 689
The ability of snapshot compressive imaging (SCI) systems to efficiently capture high-dimensional (HD) data has led to an inverse problem, which consists of recovering the HD signal from the compressed and noisy measurement. While reconstruction algo
Externí odkaz:
http://arxiv.org/abs/2201.06931