The semantics of the word “dispute” based on the seven types of Izutsu's simultaneous semantic theory by Sakineh Mosavi Asl, Shaker Ameri, Ali akbar Noresideh

“…In this research, an attempt has been made to present a more precise concept of “dispute” by relying on the seven methods of simultaneous semantics in an analytical-descriptive manner. …”
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Measuring Semantic Stability: Statistical Estimation of Semantic Projections via Word Embeddings by Roger Arnau, Ana Coronado Ferrer, Álvaro González Cortés, Claudia Sánchez Arnau, Enrique A. Sánchez Pérez

“…We present a new framework to study the stability of semantic projections based on word embeddings. Roughly speaking, semantic projections are indices taking values in the interval <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>[</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>]</mo></mrow></semantics></math></inline-formula> that measure how terms share contextual meaning with the words of a given universe. …”
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Figurative language is (implicitly) more dynamic and emotionally deeper than literal language by Tshering Yanzom Dorji, Frank H. Durgin

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Semantic models and tools for the development of artificial neural networks and their integration into knowledge bases by M. V. Kovalev

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Performance Evaluation of Artificial Neural Network Methods Based on Block Machine Learning Classification by Raya Hamdy, Mohammed Younis

“…This study proposes a block-by-block (5x5 chunks) segmentation method for semantic segmentation, which involves image dissection, feature extraction, and model training based on specific color and textural properties. …”
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Inveestigating the Potential and Foundations of Pilgrimage Rituals Based on the Understanding of the Semantic System of the Participants in the Arbaeen Walk by rezadost karim, marziyeh shahryari

“…Therefore, this study is a type of qualitative research that was conducted using the foundational data theory method to understand the semantic system of the pilgrims who participated in the walk. …”
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Fishery Web Service Composition Method Based on Ontology by Qing-mei YU, Lan WANG, Dong-mei HUANG

“…In the present paper, a heuristic web service composition method based on fishery ontology is presented, and the proposed web services are described. …”
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Weakly Supervised Deep Semantic Segmentation Using CNN and ELM with Semantic Candidate Regions by Xinying Xu, Guiqing Li, Gang Xie, Jinchang Ren, Xinlin Xie

“…To reduce the cost, the paper proposes a semantic candidate regions trained extreme learning machine (ELM) method with image-level labels to achieve pixel-level labels mapping. …”
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Image region semantic enhancement and symmetric semantic completion for text-to-image person search by Ting Tuo, Lijun Guo, Rong Zhang, Yirui Wang, Jiangbo Qian, Shangce Gao

“…In this paper, we are excited to introduce our proposed method called Image Region Semantic Enhancement and Symmetric Semantic Completion (RE-SSC). …”
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TCCFNet: a semantic segmentation method for mangrove remote sensing images based on two-channel cross-fusion networks by Lixiang Fu, Yaoru Wang, Shulei Wu, Jiasen Zhuang, Zhongqiang Wu, Jian Wu, Huandong Chen, Yukai Chen

“…However, due to the complexity of mangrove distribution and the similarity among different categories in remote sensing images, traditional image segmentation methods struggle to accurately identify mangrove regions. …”
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Identifying translation biases of cognate terms in Chinese textbooks: A GloVe-based method with semantic similarity analysis by Youjing Wang

“…To improve the accuracy of identifying translation biases in cognate terms, this study proposes a diagnostic method based on Global Vectors for Word Representation (GloVe) word embeddings and semantic similarity. …”
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Intelligent Inspection Method for Rebar Installation Quality of Reinforced Concrete Slab Based on Point Cloud Processing and Semantic Segmentation by Ruishi Wang, Jianxiong Zhang, Hongxing Qiu, Jian Sun

“…In order to solve this problem, this study uses a depth camera and aims to develop an intelligent inspection method for the rebar installation quality of an RC slab. …”
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Advances in Deep Learning for Semantic Segmentation of Low-Contrast Images: A Systematic Review of Methods, Challenges, and Future Directions by Claudio Urrea, Maximiliano Vélez

“…The semantic segmentation (SS) of low-contrast images (LCIs) remains a significant challenge in computer vision, particularly for sensor-driven applications like medical imaging, autonomous navigation, and industrial defect detection, where accurate object delineation is critical. …”
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Data enrichment for semantic segmentation of point clouds for the generation of geometric-semantic road models by David Crampen, Joerg Blankenbach

“…A Digital Twin of a built asset relies on a geometric-semantic as-is model of the area of interest, where an essential step for automated model generation is the semantic segmentation of reality capture data. …”
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The Phonograms’ Genuine‐Character Status: What the Embedded Semantic Radicals’ Semantic Activation Live by by Meng Jiang, Ya Tan, Xia Wang, Yuli Hao

“…Methods Experiment 1 was committed to confirming whether both character and non‐character semantic radicals could be semantically activated when embedded in genuine Chinese phonograms. …”
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ForestSemantic: a dataset for semantic learning of forest from close-range sensing by Xinlian Liang, Hanwen Qi, Xuejie Deng, Jianchang Chen, Shangshu Cai, Qingjun Zhang, Yunsheng Wang, Antero Kukko, Juha Hyyppä

“…Recently, Deep Learning (DL) methods were regarded as a new cornerstone of algorithm development. …”
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Evidence classification method of chat text based on DSR and BGRU model by Yu ZHANG, Binglong LI, Xuejuan LI, Heyu ZHANG

“…It is always unlikely to efficiently identify and extract chat text evidence related to criminal events, due to the complex semantics such as “slang” in the chat content and the huge amount of chat text data generated by social software such as instant messaging.Based on this motivation, a chat text evidence classification model (DSR-BGRU) based on the DSR (dynamic semantic representation) model and the BGRU (bidirectional gated recurrent unit) model was proposed.The chat text data was pre-processed to preserve the characteristics of the criminal field.Then a multi-layer chat text feature extraction and classification model using the Keras framework was proposed.With the text matrix composed of vector representation of words in the DSR model as the input vector, the input layer of the DSR model featured the chat text from the semantic level.Then the hidden layer of the BGRU model extracted the context characteristics of the text composed of the word vectors.The softmax classification layer recognized and extracted the chat text evidence.The experimental results show that the proposed DSR-BGRU can more accurately identify and extract chat records compared with other models and methods for text classification, and it can also effectively extract the criminal text information from the chat information with the accuracy rate 92.06% and the F1 score 91.00%.…”
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SPFDNet: Water Extraction Method Based on Spatial Partition and Feature Decoupling by Xuejun Cheng, Kuikui Han, Jian Xu, Guozhong Li, Xiao Xiao, Wengang Zhao, Xianjun Gao

“…Current water extraction methods aggregated richer multi-level features to enhance the output results. …”
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Analysis of Short Texts Using Intelligent Clustering Methods by Jamalbek Tussupov, Akmaral Kassymova, Ayagoz Mukhanova, Assyl Bissengaliyeva, Zhanar Azhibekova, Moldir Yessenova, Zhanargul Abuova

Subjects: “…clustering methods…”
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Learning Ordinality in Semantic Segmentation by Ricardo P. M. Cruz, Rafael Cristino, Jaime S. Cardoso

“…Semantic segmentation consists of predicting a semantic label for each image pixel. …”
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