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Metal halide perovskite nanocrystals with enhanced photoluminescence and stability toward anti-counterfeiting highperformance flexible fibers

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Nano Research 2023年第2期16卷 3542-3551页

作者： Ranran Zhou Chi-An Cheng Xuyi Wang Kun Nie Jing Wu Mengyun Wu Xiuqiang Duan Ziyao Hu Injamam Ul Huq Hua Wang Luoxin Wang Lefu Mei Haikun Liu Xiaoxue Ma School of Materials Science and Engineering Hubei Key Laboratory for New Textile Materials and ApplicationsKey Laboratory of Polyphenylene Sulfide Fiber and Application in Textile Industryand State Key Laboratory of New Textile Materials&Advanced Processing TechnologyWuhan Textile UniversityWuhan 430200China Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid Wastes National Laboratory of Mineral MaterialsSchool of Materials Science and TechnologyChina University of Geosciences(Beijing)Beijing 100083China Department of Bioengineering University of California Los AngelesLos Angeles 90095USA China Bluestar Chengrand Co. LtdHigh Tech Organic Fiber Key Laboratory of Sichuan ProvinceChengdu 610042China Department of Energy and Chemical Engineering Dongguan University of TechnologyDongguan 523808China

As a new type of light-collecting and luminescent material,all-inorganic cesium lead halide CsPbX_(3)(X=Cl,Br,I)perovskite nanocrystals(NCs)are expected to have a wide range of applications in the fields of photovoltaics,optoelectronics,and fluorescence anti-counterfeiting,***,improving the fluorescence performance and stability of CsPbX_(3)perovskite NCs to prompt their applications would promise both fundamental and practical significance for in-depth research in the field of halide *** this paper,we developed a modification strategy to introduce a halogen source,zinc bromide(ZnBr_(2))in hexane,to CsPbX_(3)perovskite that can be conducted under atmospheric conditions with reduced reaction cost and easier *** first work in this paper was to apply the modification strategy to CsPbI_(3)nanowires(NWs).Compared with the untreated NWs,the ZnBr_(2)/hexane modified CsPbI_(3)NWs exhibited better fluorescence ***,based on the study of perovskite NWs,we investigated perovskite nanocrystal-CsPbI_(3)nanorods(NRs)with different morphologies and *** was found that the luminescence properties of nanorods(NRs)were ***,we infiltrated the modified NRs into the aramid/polyphenylene sulfide(ACFs/PPS)composite paper yielded from our previous work to study its fluorescence performance for *** luminescence properties under ultraviolet light irradiation enable better performance in fluorescence *** ZnBr_(2)/hexane modification strategy and the applications studied in this work will expand the scope of perovskite research,laying the foundation for the applications of fluorescent anti-counterfeiting,nano-photoelectric devices,and fluorescent composite materials.

关键词： perovskite nanocomposites photoluminescence fluorescent anti-counterfeiting aramid/polyphenylene sulfide compound paper

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EPM-Net: A better way for optical and infrared scene matching via edge point 12

EPM-Net: A better way for optical and infrared scene matchin...

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SPIE 12th International Symposium on Multispectral Image processing and Pattern Recognition, MIPPR 2023

作者： Huang, Shixiang Chi, Longyun Fu, Wenxing Tian, Jinwen National Key Laboratory of Multispectral Information Intelligent Processing Technology Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781510674943

ISBN: (纸本)9781510674936

As a crucial auxiliary technique in inertial navigation, scene matching has been widely applied in aircraft navigation and guidance. To enhance the adaptability and efficiency of scene matching algorithms in complex environments, existing approaches have gradually shifted towards heterogeneous scene matching, such as optical/ infrared scene matching based on deep learning features, with a focus on point features. However, due to the complex and diverse nonlinear distortions between optical and infrared images, the matching accuracy often fails to meet the practical requirements of navigation and positioning. In view of this problem, an EPM-Net algorithm based on edge features is proposed to improve matching performance by extracting more stable and discriminative edge point descriptors. Experimental results on infrared datasets demonstrate that this method achieves an average matching accuracy improvement of more than four times compared to traditional and existing deep learning methods. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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An Evolutionary Multitasking Algorithm for Efficient Multiobjective Recommendations

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第3期6卷 518-532页

作者： Tian, Ye Ji, Luke Hu, Yiwei Ma, Haiping Wu, Le Zhang, Xingyi Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230601 China Anhui University Institutes of Physical Science and Information Technology Hefei230601 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Hefei230029 China

Represented by evolutionary algorithms and swarm intelligence algorithms, nature-inspired metaheuristics have been successfully applied to recommender systems and amply demonstrated effectiveness, in particular, for multiobjective recommendation. Owing to the population-based search paradigm, these algorithms can produce a number of recommendation lists, making diverse tradeoffs between multiple metrics and meeting the requirements of accuracy, novelty, diversity, and other user preferences. However, these algorithms are criticized for the low efficiency of the optimization process, especially when the number of users is large. To address this issue, this article proposes an evolutionary multitasking-based recommendation method, where each task corresponds to a user and all the tasks are optimized simultaneously, thus highly improving the efficiency of recommendation. To enhance the convergence speed, all the users are divided into multiple populations according to the similarity between their preferences, where each population evolves with internal knowledge transfer between users, and all the populations evolve with external knowledge transfer between populations. Experimental results on various datasets verify that the proposed method can better balance between multiple metrics than classical and deep neural network-based recommendation methods and exhibits significantly higher efficiency than evolutionary multiobjective optimization-based recommendation methods. © 2024 IEEE. All rights reserved.

关键词： Multiobjective optimization

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Enhancement and recovery of photoluminescence and stability by multifunctional etching ligands treatment for perovskite nanocrystals

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Journal of Energy Chemistry 2023年第1期76卷 495-502,I0013页

作者： Yang Zhao Haipeng Zeng Xueqing Cai Yingshan Zhou Yangming Jiang Xin Zheng Lin Li Shujing Zhang Long Luo Weixi Li Xiaoru Zhang Ranran Liu Wenxi Liang Rui Guo Xiong Li Michael Gratzel Center for Mesoscopic Solar Cells Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074HubeiChina State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430073HubeiChina State Key Laboratory of Functions and Applications of Medicinal Plants Guizhou Medical University Guiyang 550014GuizhouChina

Perovskite nanocrystals(PNCs)have recently become promising optoelectronic materials due to their excellent photophysical ***,the highly dynamic binding state between ligands and the surface of PNCs has severely restricted their luminescent properties and *** this work,1,3-bisbenzyl-2-oxoimidazolidine-4,5-dicarboxylic acid(cycle acid,CA)is introduced as both an etchant and a ligand upon post-synthetic surface treatment of *** removing the imperfect octahedrons[Pb X_(6)]^(4-)and passivating the surface defects synergistically,this treatment improves photoluminescence quantum yields from 76%to 95%and enhances the stability of PNCs against polar solvent,moisture,heat,and ***,CA can effectively and instantly recover the luminescence emission for aged *** a result,the CA-Cs Pb Br_(3)PNCs and CA-Cs Pb IxBr_(3-x)PNCs are applied as color-converting layers on a blue LED chip for warm white light-emitting diodes(WLEDs)with a color coordinate of(0.41,0.40).Importantly,the CA-based WLED device exhibits superior stability in operational conditions.

关键词： Perovskite nanocrystals Synergistic effect Emission recovery White light emitting diodes Stability

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Research on Improved MobileViT Image Tamper Localization Model

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Computers, Materials & Continua 2024年第8期80卷 3173-3192页

作者： Jingtao Sun Fengling Zhang Huanqi Liu Wenyan Hou School of Computer Science and Technology Xi’an University of Posts and TelecommunicationsXi’an710121China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an University of Posts and TelecommunicationsXi’an710121China

As image manipulation technology advances rapidly,the malicious use of image tampering has alarmingly escalated,posing a significant threat to social *** the realm of image tampering localization,accurately localizing limited samples,multiple types,and various sizes of regions remains a multitude of *** issues impede the model’s universality and generalization capability and detrimentally affect its *** tackle these issues,we propose FL-MobileViT-an improved MobileViT model devised for image tampering *** proposed model utilizes a dual-stream architecture that independently processes the RGB and noise domain,and captures richer traces of tampering through dual-stream ***,the model incorporating the Focused Linear Attention mechanism within the lightweight network(MobileViT).This substitution significantly diminishes computational complexity and resolves homogeneity problems associated with traditional Transformer attention mechanisms,enhancing feature extraction diversity and improving the model’s localization *** comprehensively fuse the generated results from both feature extractors,we introduce the ASPP architecture for multi-scale feature *** facilitates a more precise localization of tampered regions of various ***,to bolster the model’s generalization ability,we adopt a contrastive learning method and devise a joint optimization training strategy that leverages fused features and captures the disparities in feature distribution in tampered *** strategy enables the learning of contrastive loss at various stages of the feature extractor and employs it as an additional constraint condition in conjunction with cross-entropy *** a result,overfitting issues are effectively alleviated,and the differentiation between tampered and untampered regions is *** evaluations on five benchmark datasets(IMD-20,CASIA,NIST-16,Columbia and Coverage)validat

关键词： Image tampering localization focused linear attention mechanism MobileViT contrastive loss

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Efficient Construction of Chiral Binaphthalene-Core Phosphepine Compounds Using Palladium-Catalyzed C—P Coupling Reactions

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有机化学 2024年第12期44卷 3771-3783页

作者： Wang Cuiying Zhang Ying Zheng Jia-Lian Yuan Ji Meng Sixuan Chen Jian Yu Guang-Ao State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200 International Joint Research Center for Intelligent Biosensor Technology and Health National Key Laboratory of Green PesticidesCollege of ChemistryCentral China Normal UniversityWuhan 430079

Binaphthalene-core phosphepine compounds with axial chirality belong to an important class of organocatalysts and ligands used in catalytic asymmetric ***,the number and application of these compounds have been limited due to the lack of efficient synthetic methods currently available to ***,a simple and efficient palladium-catalyzed C—P cross-coupling reaction of enantiopure(R)-1 with a variety of aryl and heteroaryl halides is *** reaction provides access to a series of chiral binaphthalene-core phosphepine compounds using Pd(OAc)2/dippf as a catalyst,which allows most products to be formed in moderate to high yields(40%~92%)with excellent ee values(90%~99%ee).

关键词： Pd catalysis chiral axially binaphthalene C-P coupling reactions

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TransCGAN-based Parameter Extraction Framework for SAR Image Simulation 2

TransCGAN-based Parameter Extraction Framework for SAR Image...

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2nd IEEE International Conference on Signal, Information and Data processing, ICSIDP 2024

作者： Deng, Sidan He, Jingfei Mao, Yongfei Zhao, Liangbo Chen, Liang Shi, Hao Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Chongqing Innovation Center Chongqing China Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China China Academy of Space Technology Institute of Remote Sensing Satellite Beijing China Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Chongqing Innovation Center Beijing China

ISBN: (纸本)9798331515669

Synthetic Aperture Radar (SAR) images have a wide range of applications due to their all-weather and all-day working conditions. However, SAR images with different scenarios and imaging conditions are insufficient or even rare, which is required in specific SAR image tasks. Fortunately, SAR image simulation technology can provide ample simulated images under these conditions at a low cost, addressing the scarcity of specific real SAR data. Accurate parameters are crucial for obtaining high-quality simulated images. However, it is time-consuming and labour-intensive to adjust parameters manually, and it often fails to achieve accurate simulation parameters. To tackle this problem, this paper proposes a TransCGAN-based SAR image simulation method that combines deep learning with traditional methods. By training TransCGAN, a conditional generative adversarial network (CGAN) integrated with Transformer architecture, a mapping between SAR images and simulation parameters is established. This enables the extraction of simulation parameters directly from the real SAR image, guided by the corresponding real SAR image. Ultimately, the parameters are subsequently converted into simulated SAR images via simulation software. Experimental results demonstrate that our TransCGAN-based method can effectively extract accurate simulation parameters from real SAR images, resulting in simulated images holding high similarity to real images. © 2024 IEEE.

关键词： Generative adversarial networks

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DFIMat: Decoupled Flexible Interactive Matting in Multi-person Scenarios 17th

DFIMat: Decoupled Flexible Interactive Matting in Multi-per...

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17th Asian Conference on Computer Vision, ACCV 2024

作者： Jiao, Siyi Zeng, Wenzheng Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9789819609710

Interactive portrait matting refers to extracting the soft portrait from a given image that best meets the user’s intent through their inputs. Existing methods often underperform in complex scenarios, mainly due to three factors. (1) Most works apply a tightly coupled network that directly predicts matting results, lacking interpretability and resulting in inadequate modeling. (2) Existing works are limited to a single type of user input, which is ineffective for intention understanding and also inefficient for user operation. (3) The multi-round characteristics have been under-explored, which is crucial for user interaction. To alleviate these limitations, we propose DFIMat, a decoupled framework that enables flexible interactive matting. Specifically, we first decouple the task into 2 sub-ones: localizing target instances by understanding scene semantics and the flexible user inputs, and conducting refinement for instance-level matting. We observe a clear performance gain from decoupling, as it makes sub-tasks easier to learn, and the flexible multi-type input further enhances both effectiveness and efficiency. DFIMat also considers the multi-round interaction property, where a contrastive reasoning module is designed to enhance cross-round refinement. Another limitation for multi-person matting task is the lack of training data. We address this by introducing a new synthetic data generation pipeline that can generate much more realistic samples than previous arts. A new large-scale dataset SMPMat is subsequently established. Experiments verify the significant superiority of DFIMat. With it, we also investigate the roles of different input types, providing valuable principles for users. Our code and dataset will be public. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Large datasets

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Adaptive Spatial Modeling and Multi-Scale Attention Aggregation for Semantic Segmentation of Remote Sensing Images 2

Adaptive Spatial Modeling and Multi-Scale Attention Aggregat...

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2nd IEEE International Conference on Signal, Information and Data processing, ICSIDP 2024

作者： Yang, Wenying Zhang, Yuchuan Jin, Yuxuan Wang, Yupei Chen, Liang Beijing Institute of Technology Chongqing Innovation Center National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Chongqing China Jianghan University School of Artificial Intelligence Wuhan China Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China Beijing Institute of Technology Chongqing Innovation Center Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China

ISBN: (纸本)9798331515669

As remote sensing technology advances and high-resolution sensors are deployed, the analysis of high-resolution remote sensing images encounters challenging issues, such as intra-class variability, and inter-class similarity, due to the unobvious appearance and complicated background. The high-resolution remote sensing images pose critical issues for precise semantic segmentation due to these fundamental issues. To this end, we propose an adaptive hierarchical aggregation network. Different from the previous approach of modeling semantic interdependencies solely within a single feature map in the channel dimension, we introduce multi-scale channel-wise feature aggregation to capture global contextual dependencies. Meanwhile, we design an adaptive detail-aware module to model long-range spatial dependencies, adaptively extracting effective details from different levels as compensation. Additionally, this module utilizes depth-wise separable convolution to selectively filter out irrelevant spatial details from lower-level feature maps. The outputs of the two modules are fused layer by layer to achieve refined feature representation, thereby generating precise pixel-level segmentation results. Our experiments are conducted on the Vaihingen dataset and the Potsdam dataset. The experimental results demonstrate that the proposed algorithm surpasses several existing state-of-the-art approaches. © 2024 IEEE.

关键词： Semantic Segmentation

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Self-distilled Dual-Network with Pixel Screening Loss for Blind Image Deblurring 27th

Self-distilled Dual-Network with Pixel Screening Loss for ...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Li, Tianyi Tian, Ming Gao, Changxin Sang, Nong National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9783031781247

In the field of image processing, blind image deblurring aims to restore sharp details in images blurred by an unknown convolution kernel. Recent advancements have shown that deep networks can act as effective image generative priors (DIP) for restoring clear images without requiring external datasets. However, the inherent non-uniqueness of solutions in blind image deblurring often leads DIP-based methods to converge on local optima, resulting in over- or under-deblurred images. To overcome this limitation, we propose a novel deblurring framework featuring dual image generators. These generators mutually constrain each other during training, guiding the model towards the optimal solution. Building on our network structure, we employ a self-ensemble and self-distillation strategy to guide network training, further enhancing performance. Additionally, we introduce a novel loss function based on a pixel screening method, which focuses on the important pixels. This loss enables the network to model the blur kernel more accurately and facilitates the restoration of image details. Our experiments demonstrate that our deblurring approach outperforms most existing methods both qualitatively and quantitatively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Restoration

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