Relevant bibliographies by topics / Attention based models

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Attention based models'

Author: Grafiati
Published: 24 June 2021
Last updated: 29 July 2025

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Journal articles on the topic "Attention based models"

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Zang, Yubin, Zhenming Yu, Kun Xu, Minghua Chen, Sigang Yang, and Hongwei Chen. "Fiber communication receiver models based on the multi-head attention mechanism." Chinese Optics Letters 21, no. 3 (2023): 030602. http://dx.doi.org/10.3788/col202321.030602.

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Qin, Chu-Xiong, and Dan Qu. "Towards Understanding Attention-Based Speech Recognition Models." IEEE Access 8 (2020): 24358–69. http://dx.doi.org/10.1109/access.2020.2970758.

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Cha, Peter, Paul Ginsparg, Felix Wu, Juan Carrasquilla, Peter L. McMahon, and Eun-Ah Kim. "Attention-based quantum tomography." Machine Learning: Science and Technology 3, no. 1 (2021): 01LT01. http://dx.doi.org/10.1088/2632-2153/ac362b.

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Abstract With rapid progress across platforms for quantum systems, the problem of many-body quantum state reconstruction for noisy quantum states becomes an important challenge. There has been a growing interest in approaching the problem of quantum state reconstruction using generative neural network models. Here we propose the ‘attention-based quantum tomography’ (AQT), a quantum state reconstruction using an attention mechanism-based generative network that learns the mixed state density matrix of a noisy quantum state. AQT is based on the model proposed in ‘Attention is all you need’ by Va
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Thapa, Krishu K., Bhupinderjeet Singh, Supriya Savalkar, Alan Fern, Kirti Rajagopalan, and Ananth Kalyanaraman. "Attention-Based Models for Snow-Water Equivalent Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (2024): 22969–75. http://dx.doi.org/10.1609/aaai.v38i21.30337.

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Snow Water-Equivalent (SWE)—the amount of water available if snowpack is melted—is a key decision variable used by water management agencies to make irrigation, flood control, power generation, and drought management decisions. SWE values vary spatiotemporally—affected by weather, topography, and other environmental factors. While daily SWE can be measured by Snow Telemetry (SNOTEL) stations with requisite instrumentation, such stations are spatially sparse requiring interpolation techniques to create spatiotemporal complete data. While recent efforts have explored machine learning (ML) for SW
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Fallahnejad, Zohreh, and Hamid Beigy. "Attention-based skill translation models for expert finding." Expert Systems with Applications 193 (May 2022): 116433. http://dx.doi.org/10.1016/j.eswa.2021.116433.

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Steelman, Kelly S., Jason S. McCarley, and Christopher D. Wickens. "Theory-based Models of Attention in Visual Workspaces." International Journal of Human–Computer Interaction 33, no. 1 (2016): 35–43. http://dx.doi.org/10.1080/10447318.2016.1232228.

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王, 紫阳. "Wind Speed Prediction Based on Attention-Combined Models." Artificial Intelligence and Robotics Research 14, no. 02 (2025): 389–96. https://doi.org/10.12677/airr.2025.142038.

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AlOmar, Ban, Zouheir Trabelsi, and Firas Saidi. "Attention-Based Deep Learning Modelling for Intrusion Detection." European Conference on Cyber Warfare and Security 22, no. 1 (2023): 22–32. http://dx.doi.org/10.34190/eccws.22.1.1172.

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Cyber-attacks are becoming increasingly sophisticated, posing more significant challenges to traditional intrusion detection methods. The inability to prevent intrusions could compromise the credibility of security services, thereby putting data confidentiality, integrity, and availability at risk. In response to this problem, research has been conducted to apply deep learning (DL) models to intrusion detection, leveraging the new era of AI and the proven efficiency of DL in many fields. This study proposes a new intrusion detection system (IDS) based on DL, utilizing attention-based long shor
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Tangsali, Rahul, Swapnil Chhatre, Soham Naik, Pranav Bhagwat, and Geetanjali Kale. "Evaluating Performances of Attention-Based Merge Architecture Models for Image Captioning in Indian Languages." Journal of Image and Graphics 11, no. 3 (2023): 294–301. http://dx.doi.org/10.18178/joig.11.3.294-301.

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Image captioning is a growing topic of research in which numerous advancements have been made in the past few years. Deep learning methods have been used extensively for generating textual descriptions of image data. In addition, attention-based image captioning mechanisms have also been proposed, which give state-ofthe- art results in image captioning. However, many applications and analyses of these methodologies have not been made in the case of languages from the Indian subcontinent. This paper presents attention-based merge architecture models to achieve accurate captions of images in fou
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Kong, Phutphalla, Matei Mancas, Bernard Gosselin, and Kimtho Po. "DeepRare: Generic Unsupervised Visual Attention Models." Electronics 11, no. 11 (2022): 1696. http://dx.doi.org/10.3390/electronics11111696.

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Visual attention selects data considered as “interesting” by humans, and it is modeled in the field of engineering by feature-engineered methods finding contrasted/surprising/unusual image data. Deep learning drastically improved the models efficiency on the main benchmark datasets. However, Deep Neural Networks-based (DNN-based) models are counterintuitive: surprising or unusual data are by definition difficult to learn because of their low occurrence probability. In reality, DNN-based models mainly learn top-down features such as faces, text, people, or animals which usually attract human at
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Dissertations / Theses on the topic "Attention based models"

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Belkacem, Thiziri. "Neural models for information retrieval : towards asymmetry sensitive approaches based on attention models." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30167.

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Ce travail se situe dans le contexte de la recherche d'information (RI) utilisant des techniques d'intelligence artificielle (IA) telles que l'apprentissage profond (DL). Il s'intéresse à des tâches nécessitant l'appariement de textes, telles que la recherche ad-hoc, le domaine du questions-réponses et l'identification des paraphrases. L'objectif de cette thèse est de proposer de nouveaux modèles, utilisant les méthodes de DL, pour construire des modèles d'appariement basés sur la sémantique de textes, et permettant de pallier les problèmes de l'inadéquation du vocabulaire relatifs aux représe
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Saifullah, Mohammad. "Biologically-Based Interactive Neural Network Models for Visual Attention and Object Recognition." Doctoral thesis, Linköpings universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79336.

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The main focus of this thesis is to develop biologically-based computational models for object recognition. A series of models for attention and object recognition were developed in the order of increasing functionality and complexity. These models are based on information processing in the primate brain, and specially inspired from the theory of visual information processing along the two parallel processing pathways of the primate visual cortex. To capture the true essence of incremental, constraint satisfaction style processing in the visual system, interactive neural networks were used for
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Borba, Gustavo Benvenutti. "Automatic extraction of regions of interest from images based on visual attention models." Universidade Tecnológica Federal do Paraná, 2010. http://repositorio.utfpr.edu.br/jspui/handle/1/1295.

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UOL; CAPES<br>Esta tese apresenta um método para a extração de regiões de interesse (ROIs) de imagens. No contexto deste trabalho, ROIs são definidas como os objetos semânticos que se destacam em uma imagem, podendo apresentar qualquer tamanho ou localização. O novo método baseia-se em modelos computacionais de atenção visual (VA), opera de forma completamente bottom-up, não supervisionada e não apresenta restrições com relação à categoria da imagem de entrada. Os elementos centrais da arquitetura são os modelos de VA propostos por Itti-Koch-Niebur e Stentiford. O modelo de Itti-Koch-Niebur co
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Kliegl, Reinhold, Ping Wei, Michael Dambacher, Ming Yan, and Xiaolin Zhou. "Experimental effects and individual differences in linear mixed models: Estimating the relationship between spatial, object, and attraction effects in visual attention." Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2011/5685/.

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Linear mixed models (LMMs) provide a still underused methodological perspective on combining experimental and individual-differences research. Here we illustrate this approach with two-rectangle cueing in visual attention (Egly et al., 1994). We replicated previous experimental cue-validity effects relating to a spatial shift of attention within an object (spatial effect), to attention switch between objects (object effect), and to the attraction of attention toward the display centroid (attraction effect), also taking into account the design-inherent imbalance of valid and other trials. We si
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Dimitriadis, Spyridon. "Multi-task regression QSAR/QSPR prediction utilizing text-based Transformer Neural Network and single-task using feature-based models." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177186.

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With the recent advantages of machine learning in cheminformatics, the drug discovery process has been accelerated; providing a high impact in the field of medicine and public health. Molecular property and activity prediction are key elements in the early stages of drug discovery by helping prioritize the experiments and reduce the experimental work. In this thesis, a novel approach for multi-task regression using a text-based Transformer model is introduced and thoroughly explored for training on a number of properties or activities simultaneously. This multi-task regression with Transformer
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Holmström, Oskar. "Exploring Transformer-Based Contextual Knowledge Graph Embeddings : How the Design of the Attention Mask and the Input Structure Affect Learning in Transformer Models." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175400.

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The availability and use of knowledge graphs have become commonplace as a compact storage of information and for lookup of facts. However, the discrete representation makes the knowledge graph unavailable for tasks that need a continuous representation, such as predicting relationships between entities, where the most probable relationship needs to be found. The need for a continuous representation has spurred the development of knowledge graph embeddings. The idea is to position the entities of the graph relative to each other in a continuous low-dimensional vector space, so that their relati
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Klamser, Pascal. "Collective Information Processing and Criticality, Evolution and Limited Attention." Doctoral thesis, Humboldt-Universität zu Berlin, 2021. http://dx.doi.org/10.18452/23099.

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Im ersten Teil analysiere ich die Selbstorganisation zur Kritikalität (hier ein Phasenübergang von Ordnung zu Unordnung) und untersuche, ob Evolution ein möglicher Organisationsmechanismus ist. Die Kernfrage ist, ob sich ein simulierter kohäsiver Schwarm, der versucht, einem Raubtier auszuweichen, durch Evolution selbst zum kritischen Punkt entwickelt, um das Ausweichen zu optimieren? Es stellt sich heraus, dass (i) die Gruppe den Jäger am besten am kritischen Punkt vermeidet, aber (ii) nicht durch einer verstärkten Reaktion, sondern durch strukturelle Veränderungen, (iii) das Gruppenoptimum
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Wennerholm, Pia. "The Role of High-Level Reasoning and Rule-Based Representations in the Inverse Base-Rate Effect." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Universitetsbiblioteket [distributör], 2001. http://publications.uu.se/theses/91-554-5178-0/.

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Desai, Anver. "Policy agenda-setting and the use of analytical agenda-setting models for school sport and physical education in South Africa." Thesis, University of the Western Cape, 2011. http://hdl.handle.net/11394/3596.

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This study focused on policy agenda-setting models for school sport and physical education in South Africa. The primary objective was to assess and propose options for improved agenda-setting by focussing on the use of agenda-setting models and by applying it to physical education and school sport and the policy agenda of the national government. The study has shown that pertinent school sport and physical education policy issues, as supported by key role-players and principal actors, were initially not placed on the formal policy agenda of government during the research investigation period (
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Garagnani, Max. "Understanding language and attention : brain-based model and neurophysiological experiments." Thesis, University of Cambridge, 2009. https://www.repository.cam.ac.uk/handle/1810/243852.

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This work concerns the investigation of the neuronal mechanisms at the basis of language acquisition and processing, and the complex interactions of language and attention processes in the human brain. In particular, this research was motivated by two sets of existing neurophysiological data which cannot be reconciled on the basis of current psycholinguistic accounts: on the one hand, the N400, a robust index of lexico-semantic processing which emerges at around 400ms after stimulus onset in attention demanding tasks and is larger for senseless materials (meaningless pseudowords) than for matc
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Books on the topic "Attention based models"

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Sokol'skaya, Elena, and Boris Kochurov. Geoecology of the city: models of environmental quality. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1205961.

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The monograph examines the features of studying the geoecological state of urbanized territories, reveals the use of integrated assessment and mapping in urban diagnostics, and finds a solution to geoecological problems on the example of world cities that are leading in the rating for quality of life.&#x0D; The components of an information and analytical model of the urban environment for assessing the geoecological situation are described; an algorithm for a comprehensive study of the geoecological state aimed at an adequate assessment of the quality of the urban environment. Special attentio
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Odincov, Boris. Models and intelligent systems. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1060845.

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The monograph consists of three chapters, the first of which outlines the theoretical foundations of intelligent information systems. Special attention is paid to the disclosure of the term "model" as the intended meaning depends on the understanding of the material. Introduces and examines the new concepts such as the associative and intuitive knowledge while in the creation of intellectual information systems are not used. &#x0D; The second Chapter contains the analysis of problems of development of artificial intelligence (AI), developed in two directions: classical and statistical. Discuss
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Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluati
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Gruzdeva, Viktoriya, Georgiy Gruzdev, Yuliya Klyueva, and Vlada Konova. Development of the service sector based on a customer-oriented approach. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1977989.

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In the monograph, the use of the civilizational paradigm of the analysis of economic processes and phenomena allows us to consider the specifics of the functioning of the hospitality industry in the conditions of the formation of the information economy. The features of the client-oriented approach in its institutional and dynamic dimensions are revealed. Special attention is paid to inclusive technologies in the field of hospitality.&#x0D; The result of the analysis of the features of the formation of the institutional model of the hotel business in the Nizhny Novgorod region is presented. On
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Tarakanov, Andrey, A. Sumin, and A. Hvostov. Mathematical problems of decision-making in dynamic organizational systems. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1871445.

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The monograph develops the theory of decision-making in dynamic organizational systems with a complex structure in conditions of conflict and uncertainty. An overview of the current state of the theory is given. The systems are studied: hierarchical, coalition and coalition-hierarchical (hybrid). The main attention in the process of constructing mathematical models of systems is paid to the description of ways of information interaction of decision makers. At the same time, the variants of their unfavorable (conflict) and benevolent "attitude" to each other are taken into account. Two approach
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Astaf'eva, Ol'ga, Natal'ya Moiseenko, Aleksandr Kozlovskiy, Tat'yana Shemyakina, and Viktor Serov. Risk management in construction. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1842952.

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The monograph is devoted to the issues of risk management in the organizations of the investment and construction complex. The issues of risk classification are consistently considered, approaches to determining the types and types of risks are established. Attention is paid to approaches to the construction of a risk management mechanism and the specifics of the impact on the identified risks in terms of minimizing possible damage. The issues of state regulation are highlighted, a complex economic problem related to the study of the effectiveness of the chosen strategy of real investment proj
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Vavrenyuk, Aleksandr, Viktor Makarov, and Stanislav Kutepov. Operating systems. UNIX bases. INFRA-M Academic Publishing LLC., 2016. http://dx.doi.org/10.12737/11186.

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In the manual basics command interfey-are covered&#x0D; са operating systems of UNIX family. Much attention is paid&#x0D; to practical use of teams of system and opportunities of language&#x0D; programming, shell provided by a cover. In a grant vklyu-&#x0D; Chena also some sections devoted to bases administrirova-&#x0D; niya and to network means of OS. At the end of each section there are questions&#x0D; for self-checking, the appendix contains a large number at -&#x0D; mayors of writing of shell-procedures.&#x0D; The manual is addressed to the students studying the modern&#x0D; information te
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Astrahancevaa, Irina, Sergey Bobkov, Vadim Mizonov, and Sergey Boykov. Modeling of systems. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1831624.

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The textbook discusses general issues of system modeling, analytical, empirical and simulation approaches to modeling. Typical mathematical schemes used in the analytical approach, methods and tools of simulation modeling of systems are given. Attention is also paid to network and agent-based alternative approaches to modeling.&#x0D; Meets the requirements of the federal state educational standards of higher education of the latest generation.&#x0D; It is intended for undergraduate students studying in the direction of 09.03.02 "Information systems and technologies", whose working curricula in
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Rubtsov, Nickolai, Mikhail Alymov, Alexander Kalinin, Alexey Vinogradov, Alexey Rodionov, and Kirill Troshin. Remote studies of combustion and explosion processes based on optoelectronic methods. AUS PUBLISHERS, 2022. http://dx.doi.org/10.26526/monography_62876066a124d8.04785158.

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The main objective of this book is to acquaint the reader with the main modern problems of&#x0D; the multisensor data analysis and opportunities of the hyperspectral shooting being carried out in the&#x0D; wide range of wavelengths from ultraviolet to the infrared range, visualization of the fast combustion&#x0D; processes of flame propagation and flame acceleration, the limit phenomena at flame ignition and&#x0D; propagation. The book can be useful to students of the high courses and scientists dealing with problems&#x0D; of optical spectroscopy, vizualisation, digital recognizing images and
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Naumov, Vladimir. Consumer behavior. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1014653.

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The book describes the basic issues concerning consumer behavior on the basis of the simulation of the decision-making process on buying behavior of customers in the sales area of the store and shopping Internet sites. &#x0D; The classification of models of consumer behavior, based on research in the area of economic, social and psychological theories and empirical evidence regarding decision-making by consumers when purchasing the goods, including online stores. Methods of qualitative and quantitative research of consumer behavior, fundamentals of statistical processing of empirical data. &#x
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Book chapters on the topic "Attention based models"

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Elkelany, Amany, Robert Ross, and Susan Mckeever. "WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM." In Communications in Computer and Information Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26438-2_10.

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AbstractRecently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different s
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Hommel, Sebastian, Ahmad Rabie, and Uwe Handmann. "Attention and Emotion Based Adaption of Dialog Systems." In Intelligent Systems: Models and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33959-2_12.

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Aechtner, Jonathan, Anna Wilbik, and Mirela Popa. "Assessing Aggressive Driving Behaviour Using Attention Based Models." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-74650-5_4.

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Milanova, Mariofanna, and Engin Mendi. "Attention in Image Sequences: Biology, Computational Models, and Applications." In Advances in Reasoning-Based Image Processing Intelligent Systems. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24693-7_6.

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Roussinov, Dmitri, Serge Sharoff, and Nadezhda Puchnina. "Recognizing Semantic Relations: Attention-Based Transformers vs. Recurrent Models." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45439-5_37.

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Kazi, Anees, Shadi Albarqouni, Amelia Jimenez Sanchez, et al. "Automatic Classification of Proximal Femur Fractures Based on Attention Models." In Machine Learning in Medical Imaging. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67389-9_9.

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Xiao, Yao, Haoxin Ruan, Xujian Zhao, Peiquan Jin, and Xuebo Cai. "Music Emotion Recognition Using Multi-head Self-attention-Based Models." In Lecture Notes in Computer Science. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4752-2_9.

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Gajbhiye, Amit, Thomas Winterbottom, Noura Al Moubayed, and Steven Bradley. "Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models." In Artificial Neural Networks and Machine Learning – ICANN 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61609-0_50.

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Caffaro, Fabio, Lorenzo Bongiovanni, and Claudio Rossi. "Geo-temporal Crime Forecasting Using a Deep Learning Attention-Based Model." In Security Informatics and Law Enforcement. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62083-6_26.

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AbstractCrime prediction is a crucial problem in law enforcement, and the ability to forecast where and when crimes are likely to occur can help police departments allocate their resources effectively and prevent crimes. In this chapter, we propose a geo-temporal crime forecasting model based on a transformer architecture. We use a public dataset from the Boston Police Department and forecast crimes in each cell of a 1 km × 1 km grid. We use an encoder–decoder structure to capture the spatiotemporal patterns of the crimes. The encoder elaborates the crimes that occurred in each cell during the
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Li, Caizi, Qianqian Tong, Xiangyun Liao, et al. "Attention Based Hierarchical Aggregation Network for 3D Left Atrial Segmentation." In Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12029-0_28.

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Conference papers on the topic "Attention based models"

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Wang, Junpeng, Chin-Chia Michael Yeh, Uday Singh Saini, and Mahashweta Das. "Visual Attention Exploration in Vision-Based Mamba Models." In 2025 IEEE 18th Pacific Visualization Conference (PacificVis). IEEE, 2025. https://doi.org/10.1109/pacificvis64226.2025.00031.

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Raj, P. V. Tharunn, Amitoj Singh Baweja, Lakshmi C, and Anu P M. "Multivariate Spatio-Temporal Forecasting using Attention-based Graph Models." In 2025 7th International Conference on Inventive Material Science and Applications (ICIMA). IEEE, 2025. https://doi.org/10.1109/icima64861.2025.11073874.

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Wu, Yaning, Nathalie Japkowicz, Sebastien Gilbert, and Roberto Corizzo. "Attention-Based Medical Knowledge Injection in Deep Image Classification Models." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10651246.

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Maddineni, Vinod Kumar, Naga Babu Koganti, and Praveen Damacharla. "Enhancing Microgrid Performance Prediction with Attention-Based Deep Learning Models." In 2024 11th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE). IEEE, 2024. https://doi.org/10.1109/icitacee62763.2024.10762767.

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Zhao, Peng, Ruicong Wang, Zijie Lin, Zexu Pan, Haizhou Li, and Xueyi Zhang. "Ensemble Deep Learning Models for EEG-Based Auditory Attention Decoding." In 2024 IEEE 14th International Symposium on Chinese Spoken Language Processing (ISCSLP). IEEE, 2024. https://doi.org/10.1109/iscslp63861.2024.10800199.

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Verlekar, Tanmay, and Prateek Upadhya. "Shallow convolution and attention-based models for micro-expression recognition." In ESANN 2025. Ciaco - i6doc.com, 2025. https://doi.org/10.14428/esann/2025.es2025-68.

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Yun, Gwang-Hyeon, and Young-Rae Cho. "Comparative Analysis of Attention-based Models for Drug-Target Interaction Prediction." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10822678.

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Disabato, Raffaele, AprilPyone MaungMaung, Huy H. Nguyen, and Isao Echizen. "Transfer-Based Adversarial Attack Against Multimodal Models by Exploiting Perturbed Attention Region." In 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2024. https://doi.org/10.1109/apsipaasc63619.2025.10849236.

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Anubhove, Md Sadik Tasrif, S. M. Masum Ahmed, Mohammad Zeyad, and Asmay Ajma Khanam Aka. "Wind Speed Forecasting for Wind Turbines Using Attention-Based Machine Learning Models." In 2024 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE). IEEE, 2024. https://doi.org/10.1109/wiecon-ece64149.2024.10915017.

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Gueriani, Afrah, Hamza Kheddar, and Ahmed Cherif Mazari. "Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models." In 2024 International Conference on Telecommunications and Intelligent Systems (ICTIS). IEEE, 2024. https://doi.org/10.1109/ictis62692.2024.10894509.

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Reports on the topic "Attention based models"

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Kumar, Kaushal, and Yupeng Wei. Attention-Based Data Analytic Models for Traffic Flow Predictions. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2211.

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Traffic congestion causes Americans to lose millions of hours and dollars each year. In fact, 1.9 billion gallons of fuel are wasted each year due to traffic congestion, and each hour stuck in traffic costs about $21 in wasted time and fuel. The traffic congestion can be caused by various factors, such as bottlenecks, traffic incidents, bad weather, work zones, poor traffic signal timing, and special events. One key step to addressing traffic congestion and identifying its root cause is an accurate prediction of traffic flow. Accurate traffic flow prediction is also important for the successfu
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Pasupuleti, Murali Krishna. Decision Theory and Model-Based AI: Probabilistic Learning, Inference, and Explainability. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv525.

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Abstract Decision theory and model-based AI provide the foundation for probabilistic learning, optimal inference, and explainable decision-making, enabling AI systems to reason under uncertainty, optimize long-term outcomes, and provide interpretable predictions. This research explores Bayesian inference, probabilistic graphical models, reinforcement learning (RL), and causal inference, analyzing their role in AI-driven decision systems across various domains, including healthcare, finance, robotics, and autonomous systems. The study contrasts model-based and model-free approaches in decision-
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Leis and Walsh. L51575 Mechanics-Based Analysis of SCC in a Carbonate-Bicarbonate Environment. Pipeline Research Council International, Inc. (PRCI), 1988. http://dx.doi.org/10.55274/r0010306.

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Stress-corrosion cracking (SCC) occurs occasionally in line-pipe steels. Reviews of this cracking indicate that the environment is carbonate-bicarbonate and that the cracking is primarily intergranular. Research sponsored by the PRCI Line Pipe Research Supervisory Committee (LPRSC) has over the years identified metallurgical and electrochemical parameters as playing a role in the process. This work has also argued the significance of strain rate and its relationship to the service loading, given that dissolution is indicated as the controlling mechanism. While much has been learned about the m
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Alonso-Robisco, Andres, and Jose Manuel Carbo. Analysis of CBDC Narrative OF Central Banks using Large Language Models. Banco de España, 2023. http://dx.doi.org/10.53479/33412.

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Central banks are increasingly using verbal communication for policymaking, focusing not only on traditional monetary policy, but also on a broad set of topics. One such topic is central bank digital currency (CBDC), which is attracting attention from the international community. The complex nature of this project means that it must be carefully designed to avoid unintended consequences, such as financial instability. We propose the use of different Natural Language Processing (NLP) techniques to better understand central banks’ stance towards CBDC, analyzing a set of central bank discourses f
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Keeney, Roman, and Thomas Hertel. GTAP-AGR: A Framework for Assessing the Implications of Multilateral Changes in Agricultural Policies. GTAP Technical Paper, 2005. http://dx.doi.org/10.21642/gtap.tp24.

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Global models of agricultural trade have a long and distinguished history. The introduction of the GTAP data base and modeling project represented a significant advance forward as it put modelers and trade policy analysts on common ground. After an initial generation of GTAP based modeling of agricultural trade policy using the standard modeling framework, individual researchers have begun introducing agricultural specificity into the standard modeling framework in order to better capture the particular features of the agricultural economy pertinent to their research questions. This technical
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Duclos, Diane, Bob Okello, Godefroid Muzalia, and Melissa Parker. Key considerations: Home-based care for mpox in Central and East Africa. Institute of Development Studies, 2025. https://doi.org/10.19088/sshap.2025.026.

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In September 2023, an outbreak of mpox caused by the monkeypox virus (MPXV) clade Ib was reported in Kamituga, a mining region in the Eastern Democratic Republic of the Congo (DRC). More cases of mpox started to be reported across the country and in neighbouring countries in the east, including Rwanda, Uganda and Burundi.1 In February 2025, the Africa Centres for Disease Control and Prevention and the Director-General of the World Health Organization (WHO) determined that the ongoing upsurge of mpox continues to be a public health emergency of international concern (as first declared in August
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Otioma, Chuks, and Iain MacNeil. Robo Advisors as a Use Case of AI Systems: Linking Responsible Business Practices, Compliance and Outcomes. University of Glasgow and University of Strathclyde, 2025. https://doi.org/10.36399/gla.pubs.351605.

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In this paper, we explore the workings of robo-advisors as an example of AI-based systems. We discuss the performance and challenges of robo-advice, as well as offer reflections on how and why robo-advice as part of the broader fintech and financial services sector intersects practices in AI systems, regulation and compliance. We draw attention to the implications for explainable AI, the role of humans in the loop, compliance and business practices. Our approach focuses on how the AI capabilities in robo-advisors can help to build responsible business practices and compliance elements into ope
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Briand, Etienne, Massimiliano Marcellino, and Dalibor Stevanovic. Inflation, Attention and Expectations. CIRANO, 2025. https://doi.org/10.54932/qxot2239.

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We investigate the role of attention in shaping inflation dynamics. To measure the general public attention, we utilize Google Trends (GT) data for keywords such as "inflation." For professional attention, we construct an indicator based on the standardized count of Wall Street Journal (WSJ) articles with "inflation" in their titles. Through empirical analysis, we show that attention significantly impacts inflation dynamics, even when accounting for traditional inflation-related factors. Macroeconomic theory suggests that expectations formation is a natural mechanism to explain these findings.
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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-c
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Rizzo, Tesalia. Shaping political trust through participatory governance in Lat in America. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003601.

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This paper critically assesses research that examines the link between participatory institutions and political trust in the context of developing countries, with a focus on Latin America. A significant limitation in the systematic accumulation of knowledge in this field is inattention to identifying a clear causal chain through which citizen participation shapes political, economic, and attitudinal outcomes such as political trust. This is particularly important in the Latin American case where constitutionally stated objectives of participatory governance include the improvement of citizen w
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