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Bin Yin on Muck Rack

Bin Yin

As seen in: Nature, Wiley Online Library, PLOS ONE, Frontiers, MDPI, BioRxiv, Canadian Journal of Infectious Diseases & Medical Microbiology, JNeurosci, PeerJ, Optica and
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Articles

CL-ODGAN: an unpaired attention-guided GAN framework for remote sensing image dehazing

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By Hongwei Zhang, Xin Mu, Bin Yin
| Nature Verified
Abstract Haze in remote sensing imagery severely degrades image quality and impedes accurate interpretation. While deep learning has advanced dehazing, its reliance on large-scale paired data is impractical for remote sensing applications. To overcome this, we propose CL-ODGAN, a novel unpaired dehazing framework built upon a systematically designed generative architecture and a dual-level contrastive learning constraint.
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Hyaluronidase Reverses the Effect of Hyaluronic Acid Without Destroying Normal Skin Structure

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By Bin Yin, Zhiling Jiang, Jian Shi
| Wiley Online Library Verified
1 Introduction Dermal fillings based on hyaluronic acid have been widely used in facial rejuvenation because of their low incidence of complications, low price, and can be reversed by hyaluronidase [1]. However, with the increase in the use of hyaluronic acid fillers, its complications are also frequently reported [2].
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Robust photon blockade with hybrid molecular optomechanics

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By Jian Tang, Baijun Li, Bin Yin, Tian-Xiang Lu, Ran Huang, Hui Jing
| Nature Verified
Abstract Molecular cavity optomechanical systems, featuring ultrahigh vibrational frequencies and strong light-matter interactions, hold significant promise for advancing applications in quantum science and technology. Specifically, by introducing metallic nanoparticles into microcavities, hybrid molecular cavity optomechanical systems can further enhance optical quality factors and system tunabilities, which enable scalable and controllable quantum platforms.
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