Relevant bibliographies by topics / Pseudo-High-Entropy

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Pseudo-High-Entropy'

Author: Grafiati
Published: 7 July 2024
Last updated: 31 July 2025

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Journal articles on the topic "Pseudo-High-Entropy"

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Zhu, Junchao, and Nan Gao. "Entropy Teacher: Entropy-Guided Pseudo Label Mining for Semi-Supervised Small Object Detection in Panoramic Dental X-Rays." Electronics 14, no. 13 (2025): 2612. https://doi.org/10.3390/electronics14132612.

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Small-scale object detection remains a significant challenge in semi-supervised object detection (SSOD), particularly in panoramic dental X-rays. Due to the small lesion size, low contrast, and complex anatomical background, conventional teacher models often fail to extract accurate lesion features, leading to noisy pseudo labels and suboptimal detection performance. Additionally, most existing SSOD methods rely on high-confidence thresholds to select pseudo labels, which may mistakenly discard valuable predictions with low scores but accurate localization—especially for small-scale targets. T
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GURMAN, Ivan, Viktor CHESHUN, Nataliia PETLIAK, Andrii DZHULIY, and Vitalii CHORNENKYI. "DETERMINATION OF ENTROPY COMPONENT IN SENSOR INDICATORS FOR GENERATION OF CRYPTOGRAPHIC KEYS OF THE MOBILE APPLICATION OF THE CLIENT-BANK SYSTEM." Herald of Khmelnytskyi National University 301, no. 5 (2021): 18–21. http://dx.doi.org/10.31891/2307-5732-2021-301-5-18-21.

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The rapid penetration of the banking market of mobile banking creates not only new opportunities and conveniences, but also new risks and threats, which leads to increased requirements for information security of mobile services. One of the important components of the security of the mobile banking service of the client-bank system is the protection mechanisms based on the use of cryptographic keys. The stability of cryptographic keys is a guarantee of system reliability and, in turn, is based on the mechanisms of generating pseudo-random numbers using primary sources of entropy, for the effec
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Jia, Xuqing, Wende Tian, Chuankun Li, Xia Yang, Zhongjun Luo, and Hui Wang. "A Dynamic Active Safe Semi-Supervised Learning Framework for Fault Identification in Labeled Expensive Chemical Processes." Processes 8, no. 1 (2020): 105. http://dx.doi.org/10.3390/pr8010105.

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A novel active semi-supervised learning framework using unlabeled data is proposed for fault identification in labeled expensive chemical processes. A principal component analysis (PCA) feature selection strategy is first given to calculate the weight of the variables. Secondly, the identification model is trained based on the obtained key process variables. Thirdly, the pseudo label confidence of identification model is dynamically optimized with an historical, current, and future pseudo label confidence mean. To increase the upper limit of the identification model that is self-learning with
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Kumar, Anil, B. Vinith, Aditya Kumar Choudhary, and Manoj Kumar Chopkar. "Synthesis and Characterization of Novel High Entropy Alloys." Materials Science Forum 978 (February 2020): 167–73. http://dx.doi.org/10.4028/www.scientific.net/msf.978.167.

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High entropy alloys (HEAs) generally exhibit either high resistance to deformation or high toughness due to the presence of body-centered or face-centered cubic structure, respectively. To overcome these limitations, new high entropy alloys have been developed in the present study. This investigation aims to synthesis and characterization of novel CoCrFeNi3Si, CoCrFe2Ni2Si, and Co2CrFeNi2Si high entropy alloys. The mechanical alloying route is used to synthesize these alloys. Grinding was carried out to 20h and X-ray diffraction (XRD) analysis was done at different time intervals of grinding.
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Inoue, A., F. L. Kong, S. L. Zhu, B. L. Shen, A. Churyumov, and W. J. Botta. "Formation, structure and properties of pseudo-high entropy clustered bulk metallic glasses." Journal of Alloys and Compounds 820 (April 2020): 153164. http://dx.doi.org/10.1016/j.jallcom.2019.153164.

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Fei, Chenyang, Xiaomei Zhang, Dayu Wang, Haomin Hu, Rong Huang, and Zejie Wang. "EPRNG: Effective Pseudo-Random Number Generator on the Internet of Vehicles Using Deep Convolution Generative Adversarial Network." Information 16, no. 1 (2025): 21. https://doi.org/10.3390/info16010021.

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With the increasing connectivity and automation on the Internet of Vehicles, safety, security, and privacy have become stringent challenges. In the last decade, several cryptography-based protocols have been proposed as intuitive solutions to protect vehicles from information leakage and intrusions. Before generating the encryption keys, a random number generator (RNG) plays an important component in cybersecurity. Several deep learning-based RNGs have been deployed to train the initial value and generate pseudo-random numbers. However, interference from actual unpredictable driving environmen
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Cui, Binge, Jiandi Cui, Yan Lu, Nannan Guo, and Maoguo Gong. "A Sparse Representation-Based Sample Pseudo-Labeling Method for Hyperspectral Image Classification." Remote Sensing 12, no. 4 (2020): 664. http://dx.doi.org/10.3390/rs12040664.

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Hyperspectral image classification methods may not achieve good performance when a limited number of training samples are provided. However, labeling sufficient samples of hyperspectral images to achieve adequate training is quite expensive and difficult. In this paper, we propose a novel sample pseudo-labeling method based on sparse representation (SRSPL) for hyperspectral image classification, in which sparse representation is used to select the purest samples to extend the training set. The proposed method consists of the following three steps. First, intrinsic image decomposition is used t
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Cui, Mengtian, Kai Li, Yulan Li, Dany Kamuhanda, and Claudio J. Tessone. "Semi-Supervised Semantic Segmentation of Remote Sensing Images Based on Dual Cross-Entropy Consistency." Entropy 25, no. 4 (2023): 681. http://dx.doi.org/10.3390/e25040681.

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Semantic segmentation is a growing topic in high-resolution remote sensing image processing. The information in remote sensing images is complex, and the effectiveness of most remote sensing image semantic segmentation methods depends on the number of labels; however, labeling images requires significant time and labor costs. To solve these problems, we propose a semi-supervised semantic segmentation method based on dual cross-entropy consistency and a teacher–student structure. First, we add a channel attention mechanism to the encoding network of the teacher model to reduce the predictive en
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Wang, Zhu, Zhe Feng, Xue-Hua Fan, and Lei Zhang. "Pseudo-passivation mechanism of CoCrFeNiMo0.01 high-entropy alloy in H2S-containing acid solutions." Corrosion Science 179 (February 2021): 109146. http://dx.doi.org/10.1016/j.corsci.2020.109146.

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Liu, Wenjie, Wenkai Zhang, Xian Sun, and Zhi Guo. "Unsupervised Cross-Scene Aerial Image Segmentation via Spectral Space Transferring and Pseudo-Label Revising." Remote Sensing 15, no. 5 (2023): 1207. http://dx.doi.org/10.3390/rs15051207.

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Unsupervised domain adaptation (UDA) is essential since manually labeling pixel-level annotations is consuming and expensive. Since the domain discrepancies have not been well solved, existing UDA approaches yield poor performance compared with supervised learning approaches. In this paper, we propose a novel sequential learning network (SLNet) for unsupervised cross-scene aerial image segmentation. The whole system is decoupled into two sequential parts—the image translation model and segmentation adaptation model. Specifically, we introduce the spectral space transferring (SST) approach to n
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Dissertations / Theses on the topic "Pseudo-High-Entropy"

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Capute, Batalha Weverson. "Alliages amorphes à pseudo-haute entropie à base de fer : structure/microstructure, corrosion et propriétés mécaniques." Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALI098.

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La quête de matériaux alternatifs pour remplacer l'acier inoxydable conventionnel dans les applications marines a récemment gagné en importance. Parmi les candidats émergents, les alliages amorphes à base de fer à faible teneur en chrome ont montré un grand potentiel, bien qu'ils nécessitent une compréhension plus approfondie de leur comportement. Cette recherche étudie l'effet de la dévitrification sur la corrosion et les propriétés mécaniques de deux compositions amorphes pseudo-entropiques novatrices à base de FeCrMoNbB et FeCrMoNiB, ainsi que leur comportement lorsqu'ils sont appliqués en
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Coucke, Alice. "Statistical modeling of protein sequences beyond structural prediction : high dimensional inference with correlated data." Thesis, Paris Sciences et Lettres (ComUE), 2016. http://www.theses.fr/2016PSLEE034/document.

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Grâce aux progrès des techniques de séquençage, les bases de données génomiques ont connu une croissance exponentielle depuis la fin des années 1990. Un grand nombre d'outils statistiques ont été développés à l'interface entre bioinformatique, apprentissage automatique et physique statistique, dans le but d'extraire de l'information de ce déluge de données. Plusieurs approches de physique statistique ont été récemment introduites dans le contexte précis de la modélisation de séquences de protéines, dont l'analyse en couplages directs. Cette méthode d'inférence statistique globale fondée sur le
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Lin, Pei Hao, and 林霈豪. "Characterization of Al-Based Lightweight Pseudo-High-Entropy Alloy Prepared by Different Ball Milling and Consolidation Routes." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/8qcgga.

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Book chapters on the topic "Pseudo-High-Entropy"

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Alvarez-Montano, Victor Emmanuel, Francisco Brown, Jorge Mata Ramírez, et al. "Design of New High Entropy Ceramics in the Pseudo-Binary System RGaO3-R2Ti2O7." In The Minerals, Metals & Materials Series. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92381-5_53.

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Alvarez-Montano, Victor Emmanuel, Francisco Brown, Jorge Mata Ramírez, et al. "Correction to: Design of New High Entropy Ceramics in the Pseudo-Binary System RGaO3-R2Ti2O7." In The Minerals, Metals & Materials Series. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92381-5_150.

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Rickard, David. "Framboid Microarchitecture." In Framboids. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190080112.003.0005.

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Framboids can be classified in terms of whether their constituent microcrystals are regularly arranged (ordered in a single domain), randomly arranged (disordered), or mixtures of both (partially ordered or multiple domains). The relative proportions of these three types are unknown, but there may be a tendency for the proportion of ordered framboids to increase with geologic age. In single domain microarchitectures the constituent microcrystals are uniform in both size and morphology and are arranged in a single array that is coherent through the framboid. Cubic close packing in these single
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Conference papers on the topic "Pseudo-High-Entropy"

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Wang, Jizhi, Jingshan Pan, and Xueli Wu. "The entropy source of pseudo random number generators: from low entropy to high entropy." In 2019 IEEE International Conference on Intelligence and Security Informatics (ISI). IEEE, 2019. http://dx.doi.org/10.1109/isi.2019.8823457.

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Liu, Jiabin, Bo Wang, Xin Shen, Zhiquan Qi, and Yingjie Tian. "Two-stage Training for Learning from Label Proportions." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/377.

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Learning from label proportions (LLP) aims at learning an instance-level classifier with label proportions in grouped training data. Existing deep learning based LLP methods utilize end-to-end pipelines to obtain the proportional loss with Kullback-Leibler divergence between the bag-level prior and posterior class distributions. However, the unconstrained optimization on this objective can hardly reach a solution in accordance with the given proportions. Besides, concerning the probabilistic classifier, this strategy unavoidably results in high-entropy conditional class distributions at the in
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Zamiri, Ali, Byung Ju Lee, and Jin Taek Chung. "Numerical Evaluation of the Unsteady Flow in a Centrifugal Compressor With Vaned Diffuser via URANS Approach." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-57538.

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The three dimensional, compressible, unsteady Navier-Stokes equations are solved to investigate the flow field of a centrifugal compressor with high compression ratio. Computational domain is consisted of an inlet bell and impeller with splitter blades followed by a two dimensional wedge vaned diffuser. The numerical method is validated by comparing the computational results with the experiments in terms of pressure ratio and compressor efficiency. The present study focuses on the unsteady pressure fluctuations and entropy production within the impeller and diffuser passages at the compressor
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Wang, Shanshan, and Lei Zhang. "Self-adaptive Re-weighted Adversarial Domain Adaptation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/440.

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Existing adversarial domain adaptation methods mainly consider the marginal distribution and these methods may lead to either under transfer or negative transfer. To address this problem, we present a self-adaptive re-weighted adversarial domain adaptation approach, which tries to enhance domain alignment from the perspective of conditional distribution. In order to promote positive transfer and combat negative transfer, we reduce the weight of the adversarial loss for aligned features while increasing the adversarial force for those poorly aligned measured by the conditional entropy. Addition
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