Image-based soft drink type classification and dietary assessment system using deep convolutional neural network with transfer learning by Rubaiya Hafiz, Mohammad Reduanul Haque, Aniruddha Rakshit, Mohammad Shorif Uddin

Subjects: “…Drinks classification…”
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Text Classification: How Machine Learning Is Revolutionizing Text Categorization by Hesham Allam, Lisa Makubvure, Benjamin Gyamfi, Kwadwo Nyarko Graham, Kehinde Akinwolere

“…Key applications of TC are explored, alongside an analysis of critical machine learning methods, including document representation techniques and dimensionality reduction strategies. Moreover, this study evaluates a range of text categorization models, identifies persistent challenges like class imbalance and overfitting, and investigates emerging trends shaping the future of the field. …”
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NoiseAugmentNet-HHO: Enhancing Histopathological Image Classification Through Noise Augmentation by Prem Purusottam Jena, Debahuti Mishra, Kaberi Das, Sashikala Mishra

“…The encoder-decoder architecture of NoiseAugmentNet-HHO ensures robust feature extraction and reconstruction, preserving spatial information essential for accurate classification. Statistical analyses confirm its superiority in maintaining image fidelity and classification accuracy. …”
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Deep Learning Model of Image Classification Using Machine Learning by Qing Lv, Suzhen Zhang, Yuechun Wang

“…Firstly, based on the analysis of the basic theory of neural network, this paper expounded the different types of convolution neural network and the basic process of its application in image classification. Secondly, based on the existing convolution neural network model, the noise reduction and parameter adjustment were carried out in the feature extraction process, and an image classification depth learning model was proposed based on the improved convolution neural network structure. …”
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A new band selection approach integrated with physical reflectance autoencoders and albedo recovery for hyperspectral image classification by V. Sangeetha, L. Agilandeeswari

“…In this study, we propose a novel approach for hyperspectral image processing, focusing on dimensionality reduction, albedo recovery, and subsequent classification. …”
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Rore: robust and efficient antioxidant protein classification via a novel dimensionality reduction strategy based on learning of fewer features by Chaolu Meng, Yongqi Hou, Quan Zou, Lei Shi, Xi Su, Ying Ju

“…Abstract In protein identification, researchers increasingly aim to achieve efficient classification using fewer features. While many feature selection methods effectively reduce the number of model features, they often cause information loss caused by merely selecting or discarding features, which limits classifier performance. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…The present study proposes an efficient DDoS attack detection model. This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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Modality-based Modeling with Data Balancing and Dimensionality Reduction for Early Stunting Detection by Yohanes Setiawan, Mohammad Hamim Zajuli Al Faroby, Mochamad Nizar Palefi Ma’ady, I Made Wisnu Adi Sanjaya, Cisa Valentino Cahya Ramadhani

“…The Synthetic Minority Oversampling Technique (SMOTE) addresses class imbalance, and Principal Component Analysis (PCA) is used for dimensionality reduction. Unimodal modeling uses tabular or image data alone, while multimodal modeling combines both before classification. …”
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Low-Complexity Microclimate Classification in Smart Greenhouses: A Fuzzy-Neural Approach by Cristian Bua, Francesco Fiorini, Michele Pagano, Davide Adami, Stefano Giordano

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Multi-Class Classification Using Improved Mahalanobis-Taguchi System Based on Binary Tree and Its Application by Niu Junlei

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Focus on Disaster Risk Reduction by ResNet-CDMV Model After Natural Disasters by Zhaojia Tang, Yu Han

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Categorization of Residential Appliances Using ZIP Load Modeling and Conservation Voltage Reduction Analysis by Mithila Seva Bala Sundaram, Wai Tong Chor, Jeyraj Selvaraj, Ab Halim Abu Bakar, ChiaKwang Tan

“…Moreover, the CVR_f value for one residence corresponds to a residential substation CVR_f which is further validated via bottom-up load model analysis. The main contribution of this paper is to categorize residential appliances based on constant impedance, constant current, and constant power through the ZIP load model and the CVR_f. …”
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Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction by Emmanuel Onah, Uche Jude Eze, Abdullahi Salahudeen Abdulraheem, Ugochukwu Gabriel Ezigbo, Kosisochi Chinwendu Amorha, Fidele Ntie-Kang

“…Conclusions Dimensionality reduction via PCA and t-SVD significantly improved model performance, particularly for LR, SVM, FNN, RF and KNN classifiers. …”
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FPGA Hardware Acceleration of AI Models for Real-Time Breast Cancer Classification by Ayoub Mhaouch, Wafa Gtifa, Mohsen Machhout

“…By adopting 8-bit fixed-point arithmetic, the design achieves a 15.8% reduction in execution time compared to traditional CPU-based implementations while maintaining high classification accuracy. …”
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Enhancing Network Security: A Study on Classification Models for Intrusion Detection Systems by Abeer Abd Alhameed Mahmood, Azhar A. Hadi, Wasan Hashim Al-Masoody

“…This study leverages AI methods to develop nine classification models using supervised machine learning classifiers. …”
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TS-Resformer: a model based on multimodal fusion for the classification of music signals by Yilin Zhang

“…Aiming at the problems of loss of time information, insufficient feature extraction, and low classification accuracy in music genre classification, firstly, we propose a Res-Transformer model that fuses the residual network with the Transformer coding layer. …”
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COMPARATIVE ANALYSIS OF CLASSIFICATION MODELS FOR DETERMINING THE QUALITY OF WINE BY ITS CHEMICAL COMPOSITION by Vladimir S. Repkin, Artemy V. Li, Grigory Yu. Semenov, Nikita I. Sermavkin, Alexander S. Kovalenko, Nikolai S. Egoshin

“…Methods: machine learning methods for the formation of classification models; statistical methods for assessing the quality of classification and comparing classifiers. …”
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Advancing e-waste classification with customizable YOLO based deep learning models by P. Akhil Rajeev, Vivek Dharewa, D. Lakshmi, G. Vishnuvarthanan, Jayant Giri, T. Sathish, Mubarak Alrashoud

“…To address these critical environmental and health implications, this research delves into a comprehensive analysis of three cutting-edge object detection models: YOLOv5, YOLOv7, and YOLOv8. These models are examined through the lens of efficient e-waste classification, a pivotal step in recycling and repurposing efforts. …”
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Joint feature selection and classification of low-resolution satellite images using the SAT-6 dataset by Rajalaxmi Padhy, Sanjit Kumar Dash, Jibitesh Mishra

“…This reduction in feature space is important because it reduces computational complexity and enhances the interpretability of the model. …”
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Efficient Fault Diagnosis of Elevator Cabin Door Drives Using Machine Learning with Data Reduction for Reliable Transmission by Jakub Gęca, Dariusz Czerwiński, Bartosz Drzymała, Krzysztof Kolano

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