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Littérature scientifique sur le sujet « Attentive Mechanisms »

Auteur : Grafiati
Publié le 9 mars 2023
Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Attentive Mechanisms"

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Yin, Wenpeng, and Hinrich Schütze. "Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms." Transactions of the Association for Computational Linguistics 6 (December 2018): 687–702. http://dx.doi.org/10.1162/tacl_a_00249.

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In NLP, convolutional neural networks (CNNs) have benefited less than recurrent neural networks (RNNs) from attention mechanisms. We hypothesize that this is because the attention in CNNs has been mainly implemented as attentive pooling (i.e., it is applied to pooling) rather than as attentive convolution (i.e., it is integrated into convolution). Convolution is the differentiator of CNNs in that it can powerfully model the higher-level representation of a word by taking into account its local fixed-size context in the input text t x. In this work, we propose an attentive convolution network,
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Spekreijse, Henk. "Pre-attentive and attentive mechanisms in vision." Vision Research 40, no. 10-12 (2000): 1179–82. http://dx.doi.org/10.1016/s0042-6989(00)00060-2.

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Von Grünau, M. W. "Attentive mechanisms in visual search." Spatial Vision 17, no. 4 (2004): 353–71. http://dx.doi.org/10.1163/1568568041920177.

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Tervaniemi, Mari. "215 Pre-attentive and attentive brain mechanisms of complex-sound perception." International Journal of Psychophysiology 30, no. 1-2 (1998): 85. http://dx.doi.org/10.1016/s0167-8760(98)90215-x.

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Jaaskelainen, Iiro P., Giorgio Bonmassar, Hennifer Melcher, et al. "Cortical mechanisms of pre-attentive auditory “Gating”." NeuroImage 13, no. 6 (2001): 321. http://dx.doi.org/10.1016/s1053-8119(01)91664-7.

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Milanese, Ruggero. "Attentive mechanisms for dynamic and static scene analysis." Optical Engineering 34, no. 8 (1995): 2428. http://dx.doi.org/10.1117/12.205668.

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YU, YUANLONG, GEORGE K. I. MANN, and RAYMOND G. GOSINE. "A SINGLE-OBJECT TRACKING METHOD FOR ROBOTS USING OBJECT-BASED VISUAL ATTENTION." International Journal of Humanoid Robotics 09, no. 04 (2012): 1250030. http://dx.doi.org/10.1142/s0219843612500302.

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It is a quite challenging problem for robots to track the target in complex environment due to appearance changes of the target and background, large variation of motion, partial and full occlusion, motion of the camera and so on. However, humans are capable to cope with these difficulties by using their cognitive capability, mainly including the visual attention and learning mechanisms. This paper therefore presents a single-object tracking method for robots based on the object-based attention mechanism. This tracking method consists of four modules: pre-attentive segmentation, top-down atten
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Sleem, Ahmed, and Ibrahim Elhenawy. "An Attentive Convolutional Recurrent Network for Fake News Detection." International Journal of Advances in Applied Computational Intelligence 2, no. 1 (2023): 08–14. http://dx.doi.org/10.54216/ijaaci.020101.

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With the rapid growth of social media and online news platforms, the spread of fake news has become a major problem, leading to misinformation and distrust. In this paper, we propose an attentive convolutional recurrent network (ACRN) for fake news detection, which combines convolutional learning and recurrent learning capabilities to capture both local and global temporal information. Additionally, we incorporate attention mechanisms to focus on important features and reduce noise. We evaluate our model on a publicly available dataset and compare it with state-of-the-art methods. The results
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Himabindu, Dakshayani D., and Praveen S. Kumar. "A Streamlined Attention Mechanism for Image Classification and Fine-Grained Visual Recognition." MENDEL 27, no. 2 (2021): 59–67. http://dx.doi.org/10.13164/mendel.2021.2.059.

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In the recent advancements attention mechanism in deep learning had played a vital role in proving better results in tasks under computer vision. There exists multiple kinds of works under attention mechanism which includes under image classification, fine-grained visual recognition, image captioning, video captioning, object detection and recognition tasks. Global and local attention are the two attention based mechanisms which helps in interpreting the attentive partial. Considering this criteria, there exists channel and spatial attention where in channel attention considers the most attent
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Kalaska, John F. "Central Neural Mechanisms of Touch and Proprioception." Canadian Journal of Physiology and Pharmacology 72, no. 5 (1994): 542–45. http://dx.doi.org/10.1139/y94-078.

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The argument is made that somesthesia is not a strictly passive process, and its central neuronal mechanisms cannot be studied in all their complexity and subtlety by applying passive stimuli to uninterested or unconscious animals. The case is clear for kinesthesia. Peripheral proprioceptive signals are altered by active muscle contractions, and the central mechanisms of kinesthetic sensations should be studied during active movements. A similar case can be made for tactile discrimination. Ascending tactile afferents are subject to modulation during movement. Moreover, the generation of a cent
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Thèses sur le sujet "Attentive Mechanisms"

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PROIETTI, VALENTINA MARIA. "How early and later-acquired experience affects the age bias in face recognition: an exploration of age-of-acquisition effects." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/75273.

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In this doctoral dissertation I present some of the studies conducted during my PhD aimed to investigate how face processing abilities develop across the lifespan and how the face representation system adapts to reflect each individual's social experience. As adults we are expert at processing faces; nevertheless our ability is greater for some categories of faces than for others, giving rise to recognition biases based on social dimensions such as species, race and age. These biases have been interpreted as a result of the interaction between individual motivation and perceptual experience pr
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Fitzgerald, Marilyn. "Are attention bias and interpretation bias reflections of a single common mechanism or multiple independent mechanisms?" University of Western Australia. School of Psychology, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0052.

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There is abundant evidence of anxiety-linked threat-biased attention and anxiety-linked threat-biased interpretation (cf. Mathews & MacLeod, 1994, 2005). The present research aimed to determine whether these cognitive biases reflect a single common underlying mechanism (the Common Mechanism Account) or multiple independent underlying mechanisms (the Independent Mechanisms Account). To address this question, a battery of eight experimental tasks was developed; four tasks measured attention bias and four measured interpretation bias. Participants with different levels of trait anxiety, completed
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Kerr, John H. "Arousal mechanisms, attention and sports performance." Thesis, University of Nottingham, 1988. http://eprints.nottingham.ac.uk/10947/.

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This thesis is concerned with the relationship between arousal mechanisms, attentional processes and competitive sports performance. Theoretical interpretations of the arousal-performance relationship have traditionally followed the inverted-U hypothesis. Based on this approach, the generally accepted view in sports psychology is that high levels of arousal are detrimental to good performance. A review of the relevant psychological literature reveals the limited nature of such an approach and draws attention to alternative perspectives such as those offered by the work of Apter and that of Cox
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Gama, Nuno. "Mechanisms of multisensory integration and attention." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/40400/.

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Spatial attention is an essential mechanism that helps us perceive our surroundings by bringing into consciousness environmental occurrences or objects that may be of importance. Studies of spatial attention have classically recorded behavioural responses to targets presented in a region of space where attention had previously been allocated to. Such investigations show a behavioural facilitation at the same location due to cueing, but less in known about the effects of shifts of attention when the cued location is not the location of interest. This thesis presents seven experiments aimed at i
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Furlan, Michele. "Neural mechanisms of attention to motion." Doctoral thesis, Università degli studi di Trento, 2011. https://hdl.handle.net/11572/368674.

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Attention is thought to alter appearance by intensifying the sensory impression of the attended stimulus. Current debates are about how this increases might operate and what are the underlying neural mechanisms. Three mechanisms have been proposed to account the effect of attention: contrast gain, response gain and baseline shift. However, psychophysical and neuroimaging studies produced results that are not always consistent. We used the functional magnetic resonance imaging (fMRI) to explore how attention alters the appearance of coherently moving dots. The first experiment assessed coherenc
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Furlan, Michele. "Neural mechanisms of attention to motion." Doctoral thesis, University of Trento, 2011. http://eprints-phd.biblio.unitn.it/434/1/PhD_Thesis_Michele_Furlan.pdf.

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Attention is thought to alter appearance by intensifying the sensory impression of the attended stimulus. Current debates are about how this increases might operate and what are the underlying neural mechanisms. Three mechanisms have been proposed to account the effect of attention: contrast gain, response gain and baseline shift. However, psychophysical and neuroimaging studies produced results that are not always consistent. We used the functional magnetic resonance imaging (fMRI) to explore how attention alters the appearance of coherently moving dots. The first experiment assessed coherenc
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Owen, Adrian Mark. "Fronto-striatal mechanisms in planning and attention." Thesis, King's College London (University of London), 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302625.

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Gontrum, Johannes. "Attention Mechanisms for Transition-based Dependency Parsing." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-395491.

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Transition-based dependency parsing is known to compute the syntactic structure of a sentence efficiently, but is less accurate to predict long-distance relations between tokens as it lacks global information about the sentence. Our main contribution is the integration of attention mechanisms to replace the static token selection with a dynamic approach that takes the complete sequence into account. Though our experiments confirm that our approach fundamentally works, our models do not outperform the baseline parser. We further present a line of follow-up experiments to investigate these resul
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Kennett, Steffan Anthony. "Links in spatial attention between touch and vision." Thesis, Birkbeck (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343623.

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Santangelo, Valerio. "Multimodal investigation on spatial attention mechanisms: a model of shared attention resources (ShAR)." Doctoral thesis, La Sapienza, 2005. http://hdl.handle.net/11573/917227.

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Livres sur le sujet "Attentive Mechanisms"

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Cantoni, Virginio, Maria Marinaro, and Alfredo Petrosino, eds. Visual Attention Mechanisms. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0111-4.

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Cantoni, V. Visual Attention Mechanisms. Springer US, 2002.

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V, Cantoni, Marinaro M, and Petrosino Alfredo, eds. Visual attention mechanisms. Kluwer Academic/Plenum Publishers, 2002.

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Sabine, Maasen, ed. Mechanisms of visual attention: A cognitive neuroscience perspective. Psychology Press, 1998.

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Baruni, Jalal Kenji. Mechanisms of attention in visual cortex and the amygdala. [publisher not identified], 2016.

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1939-, Pfaff Donald W., and Kieffer Brigitte L, eds. Molecular and biophysical mechanisms of arousal, alertness, and attention. Published by Blackwell Pub. on behalf of the New York Academy of Sciences, 2008.

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International, Symposium on Attention and Performance (19th 2000 Kloster Irsee Germany). Common mechanisms in perception and action: Attention and Performance XIX. Oxford University Press, 2002.

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Joseph, Jordan. Brain mechanisms, attention-deficit, and related mental disorders: A clinical and theoretical assessment of attention-deficit. C.C. Thomas, 1992.

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L, Carstensen Laura, and Neale John M. 1943-, eds. Mechanisms of psychological influence on physical health: With special attention to the elderly. Plenum Press, 1989.

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W, Krohne Heinz, ed. Attention and avoidance: Strategies in coping with aversiveness. Hogrefe & Huber Publishers, 1993.

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Chapitres de livres sur le sujet "Attentive Mechanisms"

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Garibotto, Giovanni. "Alerting Mechanisms in Attentive Vision Systems." In Human and Machine Perception 2. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4809-6_10.

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Staffa, Mariacarla, and Paola Barra. "Multi-monitor System for Adaptive Image Saliency Detection Based on Attentive Mechanisms." In Artificial Intelligence in HCI. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35894-4_44.

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Chella, A., M. Frixione, and S. Gaglio. "Knowledge representation for robotic vision based on conceptual spaces and attentive mechanisms." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60437-5_28.

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Chang, Mark. "Attention Mechanism and Attentive World." In Foundation, Architecture, and Prototyping of Humanized AI. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/b23355-15.

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Staffa, Mariacarla, and Paola Barra. "Correction to: Multi-monitor System for Adaptive Image Saliency Detection Based on Attentive Mechanisms." In Artificial Intelligence in HCI. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35894-4_45.

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Piastra, Marco. "Fuzzy Engagement Mechanisms." In Visual Attention Mechanisms. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0111-4_10.

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Petrosino, Alfredo. "Attentional Pyramidal Neural Mechanisms." In Visual Attention Mechanisms. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0111-4_24.

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Yantis, Steven. "Neural Mechanisms of Attentional Control." In Visual Attention Mechanisms. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0111-4_14.

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Marzi, Carlo A. "Visual Attention And the Parallel Visual Pathways." In Visual Attention Mechanisms. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0111-4_1.

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Li, Zhaoping. "Saliency And Figure-Ground Effects." In Visual Attention Mechanisms. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0111-4_11.

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Actes de conférences sur le sujet "Attentive Mechanisms"

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Cossentino, Massimo, Giovanni Pilato, Guido Averna, Myrto Mylopoulos, and John Mylopoulos. "Practical Reasoning with Attention Mechanisms." In 2025 International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR). IEEE, 2025. https://doi.org/10.1109/simpar62925.2025.10979194.

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Fu, Hongtu, and Han-Cheng Hsiang. "Comprehensive Attention Mechanism: A New Attention Mechanism Integrating Global Information and Local Details." In 2025 10th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA). IEEE, 2025. https://doi.org/10.1109/icccbda64898.2025.11030463.

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Zhou, Junchen, and Pinghua Chen. "Lite-HRNet With Attention Mechanism." In 2024 IEEE International Conference on Social Computing and Networking (SocialCom). IEEE, 2024. https://doi.org/10.1109/socialcom63172.2024.00011.

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Sheryl, Teresa Stefanie, Anthonio Obert Lais, Azani Cempaka Sari, Hanis Amalia Saputri, and Andien Dwi Novika. "Text Prediction Using Attention Mechanism." In 2024 6th International Conference on Cybernetics and Intelligent System (ICORIS). IEEE, 2024. https://doi.org/10.1109/icoris63540.2024.10903949.

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Messaoud, Walid, Rim Trabelsi, Adnane Cabani, and Fatma Abdelkefi. "An Efficient Attention Mechanism Model." In 2023 IEEE International Conference Challenges and Innovations on TIC (I2CIT). IEEE, 2023. https://doi.org/10.1109/i2cit57984.2023.11004318.

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Xia, Wenxuan. "Fused attention mechanisms-based facial expression recognition." In International Conference on Electronics. Electrical and Information Engineering, edited by Shengqing Li and Bin Hu. SPIE, 2024. https://doi.org/10.1117/12.3052253.

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Reddy, Akumalla Brahma, Bach-Tung Pham, Tung-Yu Zhuang, Bima Paristao, Pao-Chi Chang, and Jia-Ching Wang. "Leveraging Attention Mechanisms for Breast Cancer Diagnosis." In 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2024. https://doi.org/10.1109/apsipaasc63619.2025.10848966.

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Wang, Wenlin, Zongyi Xing, Yingshun Liu, and Yuzhe Qiu. "YOLOv8 Traffic Sign Detection Incorporating Attention Mechanisms." In 2024 2nd International Conference on Algorithm, Image Processing and Machine Vision (AIPMV). IEEE, 2024. http://dx.doi.org/10.1109/aipmv62663.2024.10692217.

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Hu, Junzhu, Ying Lu, Quanyuan Xu, et al. "Vehicle attribute recognition methods incorporating attention mechanisms." In International Conference on Computer Application and Information Security (ICCAIS 2024), edited by Sadiq Ali Safaa, Pandey Hari Mohan, and Boussaid Farid. SPIE, 2025. https://doi.org/10.1117/12.3061715.

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Krishnan, Chetana, Shah Hussain, Denise Stanford, et al. "Attention variant mechanism for airways segmentation." In Clinical and Biomedical Imaging, edited by Barjor S. Gimi and Andrzej Krol. SPIE, 2025. https://doi.org/10.1117/12.3047339.

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Rapports d'organisations sur le sujet "Attentive Mechanisms"

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Olton, David S., Kevin Pang, and Howard Egeth. Neural Mechanisms of Attention. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada266315.

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Olton, David, Howard Egeth, and Kevin Pang. Neural Mechanisms of Attention. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada216478.

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Shulman, Gordon L. Relating Attention to Visual Mechanisms. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada206452.

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Woldorff, M. G. Brain Attention Mechanisms in Perception and Performance. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada422630.

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Chapin, John K. Cortical Mechanisms of Attention, Discrimination, and Motor Response to Somaesthetic Stimuli. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada247228.

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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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Shulman, Gordon L., and Michael I. Posner. Relating Sensitivity and Criterion Effects to the Internal Mechanisms of Visual Spatial Attention. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada197088.

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Muñoz Fernandez, Cristina, and Patricia Henriquez. IDB Environmental and Social Grievance Protocol: 2023 Annual Report. Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0013137.

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Since November 2021, when the Environmental and Social Policy Framework entered into effect, the IDB has a direct channel, at the management level, for stakeholders to contact the institution directly when they wish to file a complaint about the environmental or social performance of IDB-financed projects. The IDB Grievance Protocol is part of the IDB Group's complaint system, through which the first line of attention to users is the project-level complaint and grievance mechanism. Users can also access IDB management grievance mechanisms, and as a last resort, the Independent Consultation and
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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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Ferdaus, Md Meftahul, Mahdi Abdelguerfi, Kendall Niles, Ken Pathak, and Joe Tom. Widened attention-enhanced atrous convolutional network for efficient embedded vision applications under resource constraints. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49459.

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Onboard image analysis enables real-time autonomous capabilities for unmanned platforms including aerial, ground, and aquatic drones. Performing classification on embedded systems, rather than transmitting data, allows rapid perception and decision-making critical for time-sensitive applications such as search and rescue, hazardous environment exploration, and military operations. To fully capitalize on these systems’ potential, specialized deep learning solutions are needed that balance accuracy and computational efficiency for time-sensitive inference. This article introduces the widened att
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