CUMULATIVE LEGAL CLASSIFICATION OF AN ACT VERSUS ELIMINATIVE CONVERGENCE OF STATUTORY PROVISIONS by Emil W. Pływaczewski, Ewa Guzik-Makaruk

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Research and Implementation of Digital Media Recommendation System Based on Semantic Classification by Xiaoguang Li

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Classification of User Expressions on Social Media Using LSTM and GRU Models by I Gede Putra Mas Yusadara, I Gusti Ayu Desi Saryanti

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Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method by İbrahim Yücel Özbek, Mustafa Taha Güller, Zeynep Turanli Tosun, Nida Kumbasar, Özkan Miloğlu

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End-to-End Semantic Leaf Segmentation Framework for Plants Disease Classification by Khalil Khan, Rehan Ullah Khan, Waleed Albattah, Ali Mustafa Qamar

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Brain CT image classification based on mask RCNN and attention mechanism by Shoulin Yin, Hang Li, Lin Teng, Asif Ali Laghari, Ahmad Almadhor, Michal Gregus, Gabriel Avelino Sampedro

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Machine state classification of electric track circuit by means of logistic regression by D. V. Borisenko, I. V. Prisukhina, S. A. Lunev

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Feature selection based on Mahalanobis distance for early Parkinson disease classification by Mustafa Noaman Kadhim, Dhiah Al-Shammary, Ahmed M. Mahdi, Ayman Ibaida

“…Significant improvements in classification performance were observed across all models. …”
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Real-time classification of EEG signals using Machine Learning deployment by Swati CHOWDHURI, Satadip SAHA, Samadrita KARMAKAR, Ankur CHANDA

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Classification and functional repair and reconstruction of lip and perilabial defects following oncosurgery by CHEN Weiliang

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Deep learning empowered sensor fusion boosts infant movement classification by Tomas Kulvicius, Dajie Zhang, Luise Poustka, Sven Bölte, Lennart Jahn, Sarah Flügge, Marc Kraft, Markus Zweckstetter, Karin Nielsen-Saines, Florentin Wörgötter, Peter B. Marschik

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The JADES Transient Survey: Discovery and Classification of Supernovae in the JADES Deep Field by Christa DeCoursey, Eiichi Egami, Justin D. R. Pierel, Fengwu Sun, Armin Rest, David A. Coulter, Michael Engesser, Matthew R. Siebert, Kevin N. Hainline, Benjamin D. Johnson, Andrew J. Bunker, Phillip A. Cargile, Stephane Charlot, Wenlei Chen, Mirko Curti, Shea DeFour-Remy, Daniel J. Eisenstein, Ori D. Fox, Suvi Gezari, Sebastian Gomez, Jacob Jencson, Bhavin A. Joshi, Sanvi Khairnar, Jianwei Lyu, Roberto Maiolino, Takashi J. Moriya, Robert M. Quimby, George H. Rieke, Marcia J. Rieke, Brant Robertson, Melissa Shahbandeh, Louis-Gregory Strolger, Sandro Tacchella, Qinan Wang, Christina C. Williams, Christopher N. A. Willmer, Chris Willott, Yossef Zenati

“…Here, we present the survey, sample, search parameters, spectral energy distributions, light curves, and classifications. Even at z ≥ 2, the NIRCam data quality is high enough to allow SN classification via multiepoch light-curve fitting with confidence. …”
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Classification theorem on irreducible representations of the q-deformed algebra U′q(son) by N. Z. Iorgov, A. U. Klimyk

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Pilot scheduling algorithm based on cell classification-cross entropy for massive MIMO by Yinhui YU, Heng ZHOU, Ying YANG, Hao PAN, Jiapeng REN

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Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm by Dhea Amanda Ramadhan, Dian Ramadhani

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Concept and Classification of Functions of State Policy in the Field of Ensuring Economic Security of the State by D. O. Koshikov

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Reducing Data Volume in News Topic Classification: Deep Learning Framework and Dataset by Luigi Serreli, Claudio Marche, Michele Nitti

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Automated strabismus detection and classification using deep learning analysis of facial images by Mahsa Yarkheir, Motahhareh Sadeghi, Hamed Azarnoush, Mohammad Reza Akbari, Elias Khalili Pour

“…The proposed deep learning model achieved an accuracy of 86.38% for binary classification and 92.7% for multi-class classification. …”
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Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images by Soe Ni Ni, J. Tian, Pina Marziliano, Hong-Tym Wong

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Anxiety classification in virtual reality using biosensors: A mini scoping review. by Deniz Mevlevioğlu, Sabin Tabirca, David Murphy

“…Accuracy of anxiety classification for two-output models ranged from 75% to 96.4%; accuracy for three-output models ranged from 67.5% to 96.3%; accuracy for four-output models ranged from 38.8% to 86.3%. …”
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