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1,655 results on '"Huang Pan"'

205. LA-ViT: A Network With Transformers Constrained by Learned-Parameter-Free Attention for Interpretable Grading in a New Laryngeal Histopathology Image Dataset

Author

Huang, Pan, Xiao, Hualiang, He, Peng, Li, Chentao, Guo, Xiaodong, Tian, Sukun, Feng, Peng, Chen, Hu, Sun, Yuchun, Mercaldo, Francesco, Santone, Antonella, and Qin, Jing

Abstract

Grading laryngeal squamous cell carcinoma (LSCC) based on histopathological images is a clinically significant yet challenging task. However, more low-effect background semantic information appeared in the feature maps, feature channels, and class activation maps, which caused a serious impact on the accuracy and interpretability of LSCC grading. While the traditional transformer block makes extensive use of parameter attention, the model overlearns the low-effect background semantic information, resulting in ineffectively reducing the proportion of background semantics. Therefore, we propose an end-to-end network with transformers constrained by learned-parameter-free attention (LA-ViT), which improve the ability to learn high-effect target semantic information and reduce the proportion of background semantics. Firstly, according to generalized linear model and probabilistic, we demonstrate that learned-parameter-free attention (LA) has a stronger ability to learn highly effective target semantic information than parameter attention. Secondly, the first-type LA transformer block of LA-ViT utilizes the feature map position subspace to realize the query. Then, it uses the feature channel subspace to realize the key, and adopts the average convergence to obtain a value. And those construct the LA mechanism. Thus, it reduces the proportion of background semantics in the feature maps and feature channels. Thirdly, the second-type LA transformer block of LA-ViT uses the model probability matrix information and decision level weight information to realize key and query, respectively. And those realize the LA mechanism. So, it reduces the proportion of background semantics in class activation maps. Finally, we build a new complex semantic LSCC pathology image dataset to address the problem, which is less research on LSCC grading models because of lacking clinically meaningful datasets. After extensive experiments, the whole metrics of LA-ViT outperform those of other state-of-the-art methods, and the visualization maps match better with the regions of interest in the pathologists' decision-making. Moreover, the experimental results conducted on a public LSCC pathology image dataset show that LA-ViT has superior generalization performance to that of other state-of-the-art methods.

Published
2024
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208. Deep‐Red InP Core‐Multishell Quantum Dots for Highly Bright and Efficient Light‐Emitting Diodes.

Author

Huang, Pan, Liu, Xiaonan, Jin, Geyu, Liu, Fangze, Shen, Huaibin, and Li, Hongbo

Subjects
*QUANTUM dots, *LIGHT emitting diodes, *LED displays, *QUANTUM efficiency, *CHARGE carriers, *BAND gaps, *QUANTUM dot LEDs
Abstract

InP‐based quantum dots (QDs) are one of the most promising heavy‐metal‐free materials for light‐emitting applications to substitute cadmium‐analogous QDs. With a bulk band gap of 1.35 eV, InP QDs can be made to emit light in the deep red and even near‐infrared region by adjusting the size. Deep‐red light‐emitting diodes (LEDs) are of great interest for promoting the growth of plants and accurate red LED displays. However, the synthesis and the fabrication of InP‐based quantum‐dot LEDs (QLEDs) emitting in the deep red region are still under development. Here, the study reports deep‐red InP/ZnSe/ZnSeS/ZnS core‐shell QDs with a photoluminescence (PL) emission peak at 680 nm and a PL quantum yield up to 95%, which is the highest among reported deep‐red QDs. Multi‐shell with a transition layer of ZnSeS is realized to decrease the lattice mismatch in the shell and increase the shell thickness, which efficiently confines charge carriers and reduces non‐radiative recombinations. In addition, the core‐shell InP QLED achieves a high luminescence of 2263 cd m−2 and an external quantum efficiency up to 6.5%. This report provides a new strategy for promoting the development of deep‐red QLEDs for next‐generation lighting and display devices. [ABSTRACT FROM AUTHOR]

Published
2023
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220. Dicyclopentadithienothiophene (DCDTT)-based organic semiconductor assisted grain boundary passivation for highly efficient and stable perovskite solar cells

Author

Shakil N. Afraj, Arulmozhi Velusamy, Chung-Yu Chen, Jen-Shyang Ni, Yamuna Ezhumalai, Chun-Huang Pan, Kuan-Yu Chen, Shueh-Lin Yau, Cheng-Liang Liu, Chien-Hung Chiang, Chun-Guey Wu, and Ming-Chou Chen

Subjects
Renewable Energy, Sustainability and the Environment, General Materials Science, General Chemistry
Abstract

New dicyclopentadithienothiophene (DCDTT) based non-fullerene acceptors 1–3 are introduced into PSC films. The INCl-DCDTT−perovskite hybrid film exhibits an excellent power conversion efficiency of 21.39%.

Published
2022

221. Post-synthesis of MSE-type titanosilicates by interzeolite transformation for selective anisole hydroxylation

Author

Rusi Peng, Huang Pan, Xintong Li, Shaoqing Jin, Zhendong Wang, Jingang Jiang, Weimin Yang, Hao Xu, and Peng Wu

Subjects
Catalysis
Abstract

MSE-type titanosilicate was efficiently post-synthesized by the combination of interzeolite transformation by siliceous Beta, dealumination and isomorphous substitution of Ti, and it exhibited high catalytic activity in anisole hydroxylation.

Published
2022

226. Experimental and Theoretical Studies of the Corrosion Inhibition Performance of Fatty Acid-based Ionic Liquids for Mild Steel in 1 M HCl: Effects of the Varied Alkyl Chain Length in the Anionic Group

Author

Wang, Shaoyan, primary, Jia, Han, additional, Wang, Qiuxia, additional, Yan, Hui, additional, Wei, Ziwei, additional, Wen, Xiaolong, additional, Wang, Qiang, additional, Fan, Fangning, additional, Wen, Shijie, additional, Huang, Pan, additional, and Kang, Wanli, additional

Published
2022
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