Search Results - "Guo, Alan"

Spectral-Spatial Feature Extraction and Classification by ANN Supervised With Center Loss in Hyperspectral Imagery by Guo, Alan J. X., Zhu, Fei

“…In this paper, we propose a spectral-spatial feature extraction and classification framework based on an artificial neuron network in the context of…”
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A CNN-Based Spatial Feature Fusion Algorithm for Hyperspectral Imagery Classification by Guo, Alan J. X., Zhu, Fei

“…The shortage of training samples remains one of the main obstacles in applying the neural networks to the hyperspectral images classification. To fuse the…”
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Improving deep hyperspectral image classification performance with spectral unmixing by Guo, Alan J.X., Zhu, Fei

“…•An abundance-based multi-HSI classification method with less overfitting issue.•Convert every HSI to the abundance representation by a dataset-specific…”
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Group-based network pruning via nonlinear relationship between convolution filters by Zhang, Guanqun, Xu, Shuai, Li, Jing, Guo, Alan J. X.

“…Convolutional neural networks (CNNs) have many successful applications in various domains, but sometimes large computing resources are required. Therefore,…”
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Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules by Guo, Alan J. X., Qi, Hao

“…In recent years, the non-biological applications of DNA molecules have made considerable progress; most of these applications were performed in vitro ,…”
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Hyperspectral Image Classification With Deep Metric Learning and Conditional Random Field by Liang, Yi, Zhao, Xin, Guo, Alan J. X., Zhu, Fei

“…To improve the classification performance in the context of hyperspectral image (HSI) processing, many works have been developed based on two common…”
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A Graph Regularized Multilinear Mixing Model for Nonlinear Hyperspectral Unmixing by Li, Minglei, Zhu, Fei, Guo, Alan J. X., Chen, Jie

“…Spectral unmixing of hyperspectral images is an important issue in the fields of remote sensing. Jointly exploring the spectral and spatial information…”
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Inspired by human olfactory system: Deep-learning-assisted portable chemo-responsive dye-based odor sensor array for the rapid sensing of shrimp and fish freshness by Jiang, Chengbin, Guo, Alan J.X., Li, Yuwen, Wang, Yufan, Sun, Jianfeng, Chen, Zhizhou, Chen, Xin, Ma, Qianyun

“…[Display omitted] •Odor visualization by converting odor information into visual information through the imaging detection technology.•Adopting a novel…”
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Characterization of disinfection byproduct formation and associated changes to dissolved organic matter during solar photolysis of free available chlorine by Young, Tessora R., Li, Wentao, Guo, Alan, Korshin, Gregory V., Dodd, Michael C.

“…Solar irradiation of chlorine-containing waters enhances inactivation of chlorine-resistant pathogens (e.g., Cryptosporidium oocysts), through in situ…”
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Morphologists overestimate the nuclear‐to‐cytoplasmic ratio by Zhang, Mingjuan L., Guo, Alan X., VandenBussche, Christopher J.

“…BACKGROUND The Paris System for Reporting Urinary Cytology (TPS) has defined nuclear‐to‐cytoplasmic (N:C) ratio cutoff values for several of its…”
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Machine Learning Models Improve the Diagnostic Yield of Peripheral Blood Flow Cytometry by Zhang, M Lisa, Guo, Alan X, Kadauke, Stephan, Dighe, Anand S, Baron, Jason M, Sohani, Aliyah R

“…Abstract Objectives Peripheral blood flow cytometry (PBFC) is useful for evaluating circulating hematologic malignancies (HM) but has limited diagnostic value…”
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On 1234-nesting Kazhdan-Lusztig R-polynomials for the symmetric group by Fan, Neil J. Y., Guo, Alan J. X.

“…Let S n denote the symmetric group on {1,2,...,n}. For two permutations u,v∈S n with u≤v in the Bruhat order, let R u,v (q) and be the Kazhdan-Lusztig…”
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Cyclic sieving phenomenon in non-crossing connected graphs by Guo, Alan

“…A non-crossing connected graph is a connected graph on vertices arranged in a circle such that its edges do not cross. The count for such graphs can be made…”
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Investigation of the photoluminescent properties, scintillation behaviour and toxicological profile of various magnesium tungstate nanoscale motifs by Hurley, Nathaniel, Srinivas, Sailesh, Fang, Justin, Sun, Manli, Hong, Simon, Chien, Chia Te, Guo, Alan, Khan, Tamor A, Li, Mingxing, Cotlet, Mircea, Moretti, Federico, Bourret, Edith, Radin, Daniel, Tsirka, Stella E, Shelly, Maya, Wong, Stanislaus S

“…We have synthesized several morphologies and crystal structures of MgWO using a one-pot hydrothermal method, producing not only monoclinic stars and large…”
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A rare complication of giant pseudocyst after femoral hernia repair with mesh: A case report by Jasmine Bhinder, Boris Borges, Weidun Alan Guo

“…Hernia repair is one of the most common procedures performed by general surgeons worldwide. Rates of recurrence have significantly decreased with the use of…”
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High-Rate Locally Correctable Codes via Lifting by Guo, Alan

“…We present a general framework for constructing high-rate error correcting codes that are locally correctable (and hence locally decodable if linear) with a…”
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Factors influencing US medical students' decision to pursue surgery by Schmidt, Lauren E., MD, Cooper, Clairice A., MD, Guo, Weidun Alan, MD, PhD, FACS

“…Abstract Background Interest and applications to surgery have steadily decreased over recent years in the United States. The goal of this review is to collect…”
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Combinatorial proof of the inversion formula on the Kazhdan–Lusztig R-polynomials by Chen, William Y. C., Fan, Neil J. Y., Guo, Alan J. X., Guo, Peter L., Huang, Harry H. Y., Zhong, Michael X. X.

“…In this paper, we present a combinatorial proof of the inversion formula on the Kazhdan–Lusztig R -polynomials. This problem was raised by Brenti. As a…”
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List-Decoding Algorithms for Lifted Codes by Guo, Alan, Kopparty, Swastik

“…Lifted Reed-Solomon codes are a natural affine-invariant family of error-correcting codes, which generalize Reed-Muller codes. They were known to have…”
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Levenshtein Distance Embedding with Poisson Regression for DNA Storage by Wei, Xiang, Guo, Alan J. X, Sun, Sihan, Wei, Mengyi, Yu, Wei

“…Proceedings of the AAAI Conference on Artificial Intelligence, (2024) 38(14), 15796-15804 Efficient computation or approximation of Levenshtein distance, a…”
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