Research note: Application of convolutional neural networks for feather classification in chickens by Jiajia Niu, Tong Li, Kunlong Qi, Yang Liu, Haixuan Deng, Yujia Hu, Dan Xu, Liuting Wu, Felix Kwame Amevor, Yingjie Wang, Gang Shu, Xiaoling Zhao

“…However, the reliability of conventional manual classification methods is debated due to the intricate nature of feather color traits. …”
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Automatic social media news classification: a topic modeling approach by Daniel Amador, Carlos Gamboa-Venegas, Ernesto García, Andrés Segura-Castillo

“… Social media has modified the way that people access news and debate about public issues. Although access to a myriad of data sources can be considered an advantage, some new challenges have emerged, as issues about content legitimacy and veracity start to prevail among users. …”
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Application of bilateral fusion model based on CNN in hyperspectral image classification by Hongmin GAO, Xueying CAO, Yao YANG, Zaijun HUA, Chenming LI

“…Aiming at the issues of decreasing spatial resolution and feature loss caused by pooling operation in depth CNN-based hyperspectral image classification algorithm,a bilateral fusion block network （DFBN）composed of bilateral fusion blocks was designed.The upper structure of bilateral fusion block was constituted by 1×1 convolution and hyperlink,which was used to transfer local spatial characteristics.The lower structure was constituted by pooling layer,convolutional layer,deconvolution layer and upsampling to enhance the characteristics of efficient discrimination.Experimental results on three benchmark hyperspectral image data sets illustrate that the model is superior to other similar classification models.…”
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Sentiment Analysis on Android Applications using MediaPipe for Text Classification by Kadek Febry Ardika, Joko Dwi Santoso

“…Sentiment analysis is an important process for understanding public opinion on various issues discussed on social media. This study aims to develop an Android application that utilizes MediaPipe for text classification based on sentiment. …”
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Bayesian weighted random forest for classification of high-dimensional genomics data by Oyebayo Ridwan Olaniran, Mohd Asrul A. Abdullah

“…In this paper, a full Bayesian weighted probabilistic model is developed for random classification trees. The new model Bayesian Weighted Random Classification Forest (BWRCF) arises from the modification of the existing random classification forest in two ways. …”
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Enhanced remote sensing image feature classification using STFF-PSPNet by Haiying Li, Jiaqi Gao, Yang Liu, Chenxi Huang, Lijun Li, Liqiang Zhang

“…Abstract Semantic segmentation of remotely sensed images is crucial for urban planning and change detection, yet faces issues like sample imbalance and low data quality. …”
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Alzheimer's disease image classification based on enhanced residual attention network. by Xiaoli Li, Bairui Gong, Xinfang Chen, Hui Li, Guoming Yuan

“…By combining residual learning, attention mechanism, and soft thresholding, the feature representation ability and classification accuracy of the model have been improved. …”
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Pyramidal Part-Based Model for Partial Occlusion Handling in Pedestrian Classification by M. Thu, N. Suvonvorn

“…Pedestrian detection and classification are of increased interest in the intelligent transportation system (ITS), and among the challenging issues, we can find limitations of tiny and occluded appearances, large variation of human pose, cluttered background, and complex environment. …”
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Financial Solvency of Russian Regions in 2010-2014: Continued Classification Analysis by I. A. Vinyukov, E. V. Maevsky, P. V. Jagodowsky

“…This article is a continuation of the first work done on the State task of the Financial University of 2013 [1-3], in which the classification of the regions of the Russian Federation according to the state statistics for 2005-2011 was proposed. …”
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Politics of National Red List Classifications: Challenging the Reclassification of Araucaria araucana by Robert Petitpas

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Automatic Classification of Online Learner Reviews Via Fine-Tuned BERTs by Xieling Chen, Di Zou, Haoran Xie, Gary Cheng, Zongxi Li, Fu Lee Wang

“…This study investigated the effectiveness of fine-tuned BERT models for the automated classification of topics in online course reviews and explored the variations of these topics across different disciplines and course rating groups. …”
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Supervised methods of machine learning for email classification: a literature survey by Muath AlShaikh, Yasser Alrajeh, Sultan Alamri, Suhib Melhem, Ahmed Abu-Khadrah

“…This review delves into issues concerning spam filtering and email classification through supervised machine learning techniques, offering a comprehensive evaluation of strategies, methods, performance indicators, and the benefits and drawbacks of different research. …”
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Plant-Based Fermented Foods: Classification, Biochemical Transformations, and Health Benefits by Beini Peng, Penghui Nie, Hengyi Xu

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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

“…Therefore, emotion analysis plays a crucial role in understanding users' conditions regarding various issues and social events. This study aims to compare the performance of emotion classification models in analyzing and identifying users' emotions on social media. …”
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Cross-Modal Compositional Learning for Multilabel Remote Sensing Image Classification by Jie Guo, Shuchang Jiao, Hao Sun, Bin Song, Yuhao Chi

“…However, most existing methods struggle to effectively integrate visual features of images and high-level semantic information of labels, which limits their ability to obtain fine-grained image features with rich semantic information for classification. To address these issues, we propose a novel cross-modal compositional learning (CMCL) model for MLRSIC, which fully utilizes label information to improve classification performance. …”
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SNCA: Semi-Supervised Node Classification for Evolving Large Attributed Graphs by Faima Abbasi, Muhammad Muzammal, Qiang Qu, Farhan Riaz, Jawad Ashraf

“…The study of attributed networks is challenging due to noise, sparsity, and class imbalance issues. In this work, we consider node centrality in conjunction with edge signs to contemplate the node classification problem in attributed networks. …”
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Transformer-Driven Active Transfer Learning for Cross-Hyperspectral Image Classification by Muhammad Ahmad, Francesco Mauro, Rana Aamir Raza, Manuel Mazzara, Salvatore Distefano, Adil Mehmood Khan, Silvia Liberata Ullo

“…Hyperspectral image (HSI) classification presents inherent challenges due to high spectral dimensionality, significant domain shifts, and limited availability of labeled data. …”
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NEXT-GENERATION SEQUENCING IN CANCER: GENETIC DIAGNOSIS, RISK PREDICTION AND CLASSIFICATION by Özkan Özdemir

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TN5000: An Ultrasound Image Dataset for Thyroid Nodule Detection and Classification by Huan Zhang, Qianglin Liu, Xiaolin Han, Lijuan Niu, Weidong Sun

“…With the emergence of artificial intelligence, deep learning based methods can provide assistance to radiologists, whose performance heavily depends on the quantity and quality of training data, but current ultrasound image datasets for thyroid nodule either directly utilize the TI-RADS assessments as labels or are not publicly available. Faced with these issues, an open-access ultrasound image dataset for thyroid nodule detection and classification is proposed, i.e. the TN5000, which comprises 5,000 B-mode ultrasound images of thyroid nodule, as well as complete annotations and biopsy confirmations by expert radiologists. …”
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KFCM-PSOTD : An Imputation Technique for Missing Values in Incomplete Data Classification by Muhaimin Ilyas, Syaiful Anam, Trisilowati Trisilowati

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