A Three-Level Speech, Music, and Mixture Classifier by Abdullah I. Al-Shoshan, Atiyah Alatiyah, Khalid Al-Mashouq

“…The proposed classifier is based on the well-known zero-crossing rate (ZCR) [1] and short-time energy (STE) [2,3] algorithms, with the positive derivative and voting procedures. …”
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On the finiteness of the classifying space of diffeomorphisms of reducible three manifolds by Sam Nariman

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A new definition and three categories for classifying ecosystems by Jaime Gómez-Márquez

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Classifying Quadratic Forms Over Z2 in Three Variables by Gerard Thompson

“…The quadratic forms in three variables over the field Z2 are classified. …”
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On Delaunay’s Theorem Classifying Coincidences of Parallelohedra at Faces of Codimension 3 by A. N. Magazinov

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MC Classifier: A Classifier for 3D Mechanical Components Based on Geometric Prior Using Graph Neural Network and Attention by Zipeng Lin, Zhenguo Nie

“…Our findings suggest that MC Classifier has significant potential to advance 3D mechanical component classification. …”
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3D Model Classification Based on Bayesian Classifier with AdaBoost by Xue-Yao Gao, Kai-Peng Li, Chun-Xiang Zhang, Bo Yu

“…They can all be used to classify 3D models, but accuracy is low due to insufficient description of 3D model. …”
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Resting state EEG classifies developmental status in three-year-old children by Dhanya Parameshwaran, Supriya Bhavnani, Debarati Mukherjee, Kamal Kant Sharma, Jennifer Jane Newson, Narayan Puthanmadam Subramaniyam, Gauri Divan, Vikram Patel, Tara C. Thiagarajan

“…Here we examined whether 3 minutes of resting-state EEG (rs-EEG) recorded in 70 33–40-month-old children using a 14-channel portable EEG device in low-resource households could classify performance on five domains of developmental outcomes (cognition, receptive language, expressive language, fine motor and gross motor coordination) as measured by the Bayley’s Scale of Infant and Toddler Development, 3rd Edition (BSID-III). …”
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IOTA Three-Step Strategy for Classifying Adnexal Masses: A Systematic Review and Meta-Analysis by Juan Luis Alcázar, Francisco Vargas, Guillem Boscá, Blanca Salazar, Juan Carlos Aguilar, Cynthia Catalan, Arleana Balazs, Daniela Burky, Magdalena Pertkiewicz, José Carlos Vilches, Rodrigo Orozco

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Cross-Modal Collaboration and Robust Feature Classifier for Open-Vocabulary 3D Object Detection by Hengsong Liu, Tongle Duan

“…Given the complexity of real-world environments, research into open-vocabulary 3D object detection is essential. Therefore, this paper aims to address two key issues in this area: how to localize and classify novel objects. …”
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Comparison of MobilenetV2 and EfficiennetB3 Method to Classify Diseases on Corn Leaves by Riyadi Slamet, Mulya Rezka, Nabila Realisti Aulia

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A novel deep learning approach to classify 3D foot types of diabetic patients by Pui-ling Li, Qin-feng Xiao, Kit-lun Yick, Qi-long Liu, Li-ying Zhang

“…In this study, we propose a novel deep learning method based on DiffusionNet which incorporates a self-attention mechanism and external features to classify the foot types of diabetic patients into six categories by using simple 3D foot images directly. …”
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SVM directed machine learning classifier for human action recognition network by Dharmanna Lamani, Pramod Kumar, A Bhagyalakshmi, J. Maria Shanthi, Lakshmana Phaneendra Maguluri, Mohammad Arif, C Dhanamjayulu, Sathish Kumar. K, Baseem Khan

“…However, existing approaches such as three-dimensional convolutional neural networks (3D CNN) and two-stream neural networks (2SNN) have computational hurdles due to the significant parameterization they require. …”
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Application of microscopic image processing and artificial intelligence detecting and classifying the spores of three novel species of Trichoderma by Fatemeh Soltani Nezhad, Kamran Rahnama, Seyed Mohamad Javidan, Keyvan Asefpour Vakilian

“…In this study, a microscopic image dataset has been developed, followed by identifying and classifying the spores of three Trichoderma species including T. harzianum, T. atroviride, and T. virens using microscopic image processing techniques. …”
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A Dynamic Measurement System Based on Adaptive Clustering and Multi-Classifier by Bowen Shi, Hongjian You, Huixian Wang

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A mobile hybrid deep learning approach for classifying 3D-like representations of Amazonian lizards by Arthur Gonsales da Silva, Arthur Gonsales da Silva, Roger Pinho de Oliveira, Caio de Oliveira Bastos, Caio de Oliveira Bastos, Elena Almeida de Carvalho, Bruno Duarte Gomes

“…This tool is aimed at processing and classifying three-dimensional samples of endemic lizard species from the Amazon rainforest. …”
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The hit problem of three variables for the cohomology of the classifying space BEs as a module over the mod 3 Steenrod Algebra at some low degrees by Bich Nhu Pham, Tu Thinh Nguyen

“…We study the extended hit problem for the cohomology of the classifying space 〖BE〗_s over field F_3, P(s)=H^* 〖B(RP^∞ )〗^s=E(x_1,x_2,…,x_s )⨂F_p [y_1,y_2,…,y_s ], with s=3 at degrees d ≤10. …”
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The hit problem of three variables for the cohomology of the classifying space BEs as a module over the mod 3 Steenrod Algebra at some low degrees by Bich Nhu Pham, Tu Thinh Nguyen

“…We study the extended hit problem for the cohomology of the classifying space 〖BE〗_s over field F_3, P(s)=H^* 〖B(RP^∞ )〗^s=E(x_1,x_2,…,x_s )⨂F_p [y_1,y_2,…,y_s ], with s=3 at degrees d ≤10. …”
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How Are Pesticides Classified? by Frederick M. Fishel

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Startup Success Factors: Classifying 3H (Hustler, Hipster, Hacker) Framework using Simple Additive Weighting by Qoriah Indah Susilowati, Fatih Başçiftçi

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