Relevant bibliographies by topics / Transformeur robuste

Contents

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

Academic literature on the topic 'Transformeur robuste'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Transformeur robuste"

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Yang, Mingze, Hai Zhu, Runzhe Zhu, Fei Wu, Ling Yin, and Yuncheng Yang. "WiTransformer: A Novel Robust Gesture Recognition Sensing Model with WiFi." Sensors 23, no. 5 (2023): 2612. http://dx.doi.org/10.3390/s23052612.

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The past decade has demonstrated the potential of human activity recognition (HAR) with WiFi signals owing to non-invasiveness and ubiquity. Previous research has largely concentrated on enhancing precision through sophisticated models. However, the complexity of recognition tasks has been largely neglected. Thus, the performance of the HAR system is markedly diminished when tasked with increasing complexities, such as a larger classification number, the confusion of similar actions, and signal distortion To address this issue, we eliminated conventional convolutional and recurrent backbones a
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Huang, Hui, Hengyu Zhang, Yusen Wang, et al. "Integrated Robust Optimization for Lightweight Transformer Models in Low-Resource Scenarios." Symmetry 17, no. 7 (2025): 1162. https://doi.org/10.3390/sym17071162.

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With the rapid proliferation of artificial intelligence (AI) applications, an increasing number of edge devices—such as smartphones, cameras, and embedded controllers—are being tasked with performing AI-based inference. Due to constraints in storage capacity, computational power, and network connectivity, these devices are often categorized as operating in resource-constrained environments. In such scenarios, deploying powerful Transformer-based models like ChatGPT and Vision Transformers is highly impractical because of their large parameter sizes and intensive computational requirements. Whi
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Reddy, G. Nagarjuna, B. V. Pallavi, B. Nageswari, and K. Khudhuwanth. "A Robust Deep Vision Transformer Model For Early Diagnosis Of Alzheimers Disease." International Journal of Research Publication and Reviews 6, no. 4 (2025): 16950–59. https://doi.org/10.55248/gengpi.6.0425.16133.

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Zope, Sanika, and Nitin Zope. "Unveiling Transformer Failures: Insights from Utilities Repaired Transformers and Their Revival." International Journal of Innovative Research in Engineering and Management 12, no. 1 (2025): 52–59. https://doi.org/10.55524/ijirem.2025.12.1.8.

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Power transformer failures pose a significant challenge to power utilities, leading to service interruptions, costly repairs, and operational inefficiencies. In Maharashtra, the State Transmission Utility has observed a marked increase in transformer failures over recent years, negatively impacting service reliability and increasing operational costs. This paper investigates the root causes of these failures using Failure Mode and Effects Analysis (FMEA), supported by MATLAB-based modelling by collecting the comprehensive data related to transformer failures. The analysis focuses on identifyin
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Tummala, Bindu Madhavi, Rishitha Jaladi, Dasari Chinna Veeraiah, and Aruna Kumari Peruri. "TransUNet for Precise and Robust GI tract Segmentation in MRI Images." Journal of Image and Graphics 12, no. 3 (2024): 302–11. http://dx.doi.org/10.18178/joig.12.3.302-311.

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Medical image processing is revolutionizing Gastrointestinal (GI) cancer radiation therapy by enabling precise targeting of high X-ray beam dosages to the tumors while protecting the surrounding healthy organs. However, the manual segmentation of healthy organs at risk from MR-Linac images is a time-consuming process that can delay treatment and increase patient suffering. Deep learning-based medical image processing algorithms have the potential to automate the segmentation of organs at risk, thereby improving the accuracy and efficiency of GI cancer radiation therapy. Every day, the MR-Linac
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Chen, Ruoxi. "Transformer-KAN: Attention-Guided Kolmogorov-Arnold Networks for Robust Seismic Signal Classification." Applied and Computational Engineering 169, no. 1 (2025): 135–46. https://doi.org/10.54254/2755-2721/2025.ch24699.

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This paper introduces Transformer-KAN, an innovative model that combines the attention mechanism of Transformers with the Kolmogorov-Arnold Networks (KAN) to achieve robust seismic signal classification. Leveraging a hierarchical attention mechanism to capture both local details and global patterns of seismic waveforms, and employing learnable functional mappings in the KAN-Former module to replace conventional feedforward layers, the model achieves notable improvements in classification accuracy and noise robustness over traditional convolutional networks and standalone Transformer models. Ad
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Al-Gahtani, Saad F., Z. M. S. Elbarbary, and Shaik Mohammad Irshad. "A developed DQ control method for shunt active power filter to improve power quality in transformers." PLOS ONE 19, no. 7 (2024): e0299635. http://dx.doi.org/10.1371/journal.pone.0299635.

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Power transformers are the most important component in power system. Exposing these transformers to the harmonic distortions causes additional heat losses, insulation stress, decrease in lifetime of insulation, and reduced power factor with decrease in efficiency of the system. The lifespan of distribution transformers is influenced by the fragility of power quality in power networks. Harmonic mitigation filters with robust control technique are required to reduce the harmonic effects on power transformer. Traditionally, synchronous reference frame (DQ) is employed to control the shunt active
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Guzman-Arteaga, Santiago, Santiago Gómez-Arango, Daniel Sanin-Villa, and María del Pilar Buitrago-Villada. "Evaluating Fault Detection Techniques in Real Electrical Transformers: A Comparative Case of Study." Statistics, Optimization & Information Computing 14, no. 1 (2025): 352–72. https://doi.org/10.19139/soic-2310-5070-2446.

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Transformers are integral to the reliability of electrical networks, necessitating robust diagnostic methods for fault detection. This study conducts a comparative evaluation of three fault detection techniques using real-world data from distribution transformers. The methods analyzed include differential current analysis, correlation-based techniques, and flux linkage increments. Results demonstrate that differential current analysis exhibits the highest sensitivity (93.33\%), detecting faults at 4.41\% of the short-circuit current. Correlation-based methods follow with 86.67\% sensitivity, w
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Wei, Jiangshu, Jinrong Chen, Yuchao Wang, Hao Luo, and Wujie Li. "Improved deep learning image classification algorithm based on Swin Transformer V2." PeerJ Computer Science 9 (October 30, 2023): e1665. http://dx.doi.org/10.7717/peerj-cs.1665.

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While convolutional operation effectively extracts local features, their limited receptive fields make it challenging to capture global dependencies. Transformer, on the other hand, excels at global modeling and effectively captures global dependencies. However, the self-attention mechanism used in Transformers lacks a local mechanism for information exchange within specific regions. This article attempts to leverage the strengths of both Transformers and convolutional neural networks (CNNs) to enhance the Swin Transformer V2 model. By incorporating both convolutional operation and self-attent
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Manasa, Smt B. "Hybrid CNN-Transformer Architecture for Robust Deepfake Detection: A Keyframe-Based Evaluation." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem46782.

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Abstract - The proliferation of Deepfake content presents a significant threat to digital integrity and media authenticity. To address this challenge, we present a comprehensive evaluation of four deep learning architectures—Convolutional Neural Networks (CNN), Transformer-based models, CNN integrated with Long Short-Term Memory (CNN+LSTM), and a novel hybrid CNN–Transformer model—specifically applied to Deepfake detection using keyframes. Keyframes were extracted from the FaceForensics++ dataset, preserving high-resolution information crucial for robust detection. Each model was trained and t
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Dissertations / Theses on the topic "Transformeur robuste"

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Douzon, Thibault. "Language models for document understanding." Electronic Thesis or Diss., Lyon, INSA, 2023. http://www.theses.fr/2023ISAL0075.

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Chaque jour, les entreprises du monde entier reçoivent et traitent d'énormes volumes de documents, entraînant des coûts considérables. Pour réduire ces coûts, de grandes entreprises automatisent le traitement documentaire, visant une automatisation complète. Cette thèse se concentre sur l'utilisation de modèles d'apprentissage machine pour extraire des informations de documents. Les progrès récents en matière d'architecture de modèle, en particulier les transformeurs, ont révolutionné le domaine grâce à leur utilisation généralisée de l'attention et à l'amélioration des pré-entraînements auto-
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Sanchez, Sébastien. "Contribution à la conception de coupleurs magnétiques robustes pour convertisseurs multicellulaires parallèles." Phd thesis, Toulouse, INPT, 2015. http://oatao.univ-toulouse.fr/14499/1/sanchez_partie_1_sur_2_2.pdf.

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Face aux enjeux énergétiques actuels, l’électronique de puissance est un domaine de recherche de premier plan. La relative fragilité des composants présents dans les chaînes de conversion implique néanmoins de devoir prendre en compte la gestion des défaillances dès la phase de conception. La défaillance d'un composant est une situation hautement critique tant sur le plan de la sécurité environnante que sur le plan de l'indisponibilité du système qui en découle. Cette problématique de sûreté de fonctionnement constitue la ligne directive de ce travail de thèse, visant à imaginer, et concevoir
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Athanasius, Germane Information Technology &amp Electrical Engineering Australian Defence Force Academy UNSW. "Robust decentralised output feedback control of interconnected grid system." Awarded by:University of New South Wales - Australian Defence Force Academy, 2008. http://handle.unsw.edu.au/1959.4/39591.

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The novel contribution of the thesis is the design and implementation of decentralised output feedback power system controllers for power oscillation damping (POD) over the entire operating regime of the power system. The POD controllers are designed for the linearised models of the nonlinear power system dynamics. The linearised models are combined and treated as parameter varying switched systems. The thesis contains novel results for the controller design, bumpless switching and stability analysis of such switched systems. Use of switched controllers against the present trend of having s
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Swain, Sushree Diptimayee. "Design and Experimental Realization of Robust and Adaptive Control Schemes for Hybrid Series Active Power Filter." Thesis, 2017. http://ethesis.nitrkl.ac.in/9369/1/2017_PhD_SDSwain_512EE109.pdf.

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The degradation in power quality causes adverse economical impact on the utilities and customers. Harmonics in current and voltage are one of the most commonly known power quality issues and are solved by employing passive power filter. But these filters are designed to provide a low impedance path for harmonics and maintaining good power quality with an simplest design and low cost. However PPFs have some drawbacks such as its performance is not better for transient condition of load. So for high-quality power requirements, numerous topologies of active filters i.e. APF connected in series or
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Pradhan, Prangya Parimita. "Robust Control Schemes for a Doubly Fed Induction Generator based Wind Energy Conversion System." Thesis, 2022. http://ethesis.nitrkl.ac.in/10344/1/2022_PhD_PPPradhan_514EE1009_Robust.pdf.

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Due to many advantages, such as variable speed operation, low noise, high torque, and ease of maintenance, the Doubly Fed Induction Generator (DFIG) is extensively employed in a Wind Energy Conversion System (WECS). To control a DFIG-based WECS, active power extraction from the wind must be regulated while reactive power must be kept at zero in order to ensure unity power factor operation. A number of control algorithms for controlling the active and reactive power of WECS have been proposed in the past. A WECS is encountered with several parametric uncertainties and external disturbances. Thu
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Deng, Yu-Shiu, and 鄧宇修. "A Fast and Robust Local Descriptor Using Features in The Intensity and Transformed Domains." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/38514468834376849455.

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碩士<br>國立中興大學<br>資訊科學與工程學系<br>100<br>Feature point matching is to find out the point correspondences between two images of the same scene or object, and this task is a vital part in many images processing technique, such as image matching, object recognition, and other vision-based application. However, there often exist some different kinds of transformation between two images, and will cause bad matching result. To solve the problem, the best way is to construct local descriptor by extracting robust and invariant local feature from interest region, and that will bring out better matching resu
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"Robust Control of Wide Bandgap Power Electronics Device Enabled Smart Grid." Doctoral diss., 2017. http://hdl.handle.net/2286/R.I.46215.

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abstract: In recent years, wide bandgap (WBG) devices enable power converters with higher power density and higher efficiency. On the other hand, smart grid technologies are getting mature due to new battery technology and computer technology. In the near future, the two technologies will form the next generation of smart grid enabled by WBG devices. This dissertation deals with two applications: silicon carbide (SiC) device used for medium voltage level interface (7.2 kV to 240 V) and gallium nitride (GaN) device used for low voltage level interface (240 V/120 V). A 20 kW solid state transfor
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Books on the topic "Transformeur robuste"

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Helfont, Samuel. A Transformed Religious Landscape. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190843311.003.0009.

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This chapter begins by re-evaluating state–society relations in Iraq during the 1990s and early 2000s. It argues, along with other archival-based works, that the regime was much more robust than the literature on Iraq had suggested during this period. Then the chapter discusses a similar dynamic with regard to the relationship between religion and state. The regime had much more control over the religious landscape in the 1990s than has been stated in previous works on Iraq, but creating the regime’s system was a long, arduous process, carried out by countless officials, to co-opt, coerce, and
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Rid, Thomas, and Marc Hecker. War 2.0. Praeger Security International, 2009. http://dx.doi.org/10.5040/9798216033455.

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War 2.0: Irregular Warfare in the Information Age argues that two intimately connected grassroots trends—the rise of insurgencies and the rise of the web—are putting modern armies under huge pressure to adapt new forms of counterinsurgency to new forms of social war. After the U.S. military—transformed into a lean, lethal, computerized force—faltered in Iraq after 2003, a robust insurgency arose. Counterinsurgency became a social form of war—indeed, the U.S. Army calls it "armed social work"—in which the local population was the center of gravity and public opinion at home the critical vulnera
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Thornton, Michael Alan. Mito and the Politics of Reform in Early Modern Japan. The Rowman & Littlefield Publishing Group, 2022. https://doi.org/10.5040/9781978721265.

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This book examines early modern Mito, today an ordinary provincial capital on the outskirts of the Tokyo commuter belt, but once the headquarters of Mito Domain, one of the most consequential places in all of Japan. As one of just three senior branches of the Tokugawa family—which ruled over Japan for 260 years—Mito’s ruling family enjoyed unparalleled status and exerted enormous influence throughout its history. In the seventeenth century, its scholars produced some of early modern Japan’s most important historical scholarship. In the eighteenth century, it developed a robust and pragmatic pr
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Pearson, David. Rebel Music in the Triumphant Empire. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780197534885.001.0001.

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At the dawn of the 1990s, as the United States celebrated its victory in the Cold War and sole superpower status by waging war on Iraq and proclaiming democratic capitalism as the best possible society, the 1990s underground punk renaissance transformed the punk scene into a site of radical opposition to American empire. Nazi skinheads were ejected from the punk scene; apathetic attitudes were challenged; women, Latino, and LGBTQ participants asserted their identities and perspectives within punk; the scene debated the virtues of maintaining DIY purity versus venturing into the musical mainstr
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Woźniak, Monika, and Maria Wyke, eds. The Novel of Neronian Rome and its Multimedial Transformations. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198867531.001.0001.

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When in 1905 the Polish writer Henryk Sienkiewicz was awarded the Nobel Prize for Literature ‘for outstanding services as an epic writer’, it was his novel Quo vadis. A Narrative of the Time of Nero that motivated the committee to bestow this notable honour. The extraordinary international success of Quo vadis catapulted the author into literary stardom, placing him at the top of international league tables for the sheer quantity of his readers. But, before long, the historical novel began to detach itself from the person of its author and to become a multimedial, mass–culture phenomenon. In t
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Book chapters on the topic "Transformeur robuste"

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Barnes, John R. "Inductors and Transformers." In Robust Electronic Design Reference Book. Springer US, 2004. http://dx.doi.org/10.1007/1-4020-7830-7_9.

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Liao, Brian Hsuan-Cheng, Chih-Hong Cheng, Hasan Esen, and Alois Knoll. "Are Transformers More Robust? Towards Exact Robustness Verification for Transformers." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40923-3_8.

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Gu, Jindong, Volker Tresp, and Yao Qin. "Are Vision Transformers Robust to Patch Perturbations?" In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19775-8_24.

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Wang, Libo, Si Chen, Zhen Wang, Da-Han Wang, and Shunzhi Zhu. "Graph Attention Transformer Network for Robust Visual Tracking." In Communications in Computer and Information Science. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1639-9_14.

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Zhang, Yaning, Tianyi Wang, Minglei Shu, and Yinglong Wang. "A Robust Lightweight Deepfake Detection Network Using Transformers." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20862-1_20.

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Mvula, Paul K., Paula Branco, Guy-Vincent Jourdan, and Herna L. Viktor. "HEART: Heterogeneous Log Anomaly Detection Using Robust Transformers." In Discovery Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45275-8_45.

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Pande, Jay, Wookhee Min, Randall D. Spain, Jason D. Saville, and James Lester. "Robust Team Communication Analytics with Transformer-Based Dialogue Modeling." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36272-9_52.

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Najari, Naji, Samuel Berlemont, Grégoire Lefebvre, Stefan Duffner, and Christophe Garcia. "RESIST: Robust Transformer for Unsupervised Time Series Anomaly Detection." In Advanced Analytics and Learning on Temporal Data. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-24378-3_5.

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Peiris, Himashi, Munawar Hayat, Zhaolin Chen, Gary Egan, and Mehrtash Harandi. "A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16443-9_16.

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Biradar, Kuldeep, Dinesh Kumar Tyagi, Ramesh Babu Battula, and P. Subbarao. "Robust Anomaly Detection Through Transformer-Encoded Feature Diversity Learning." In Lecture Notes in Computer Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2641-0_8.

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Conference papers on the topic "Transformeur robuste"

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Verma, Akshra, and Ashima Yadav. "Leveraging Swin Transformer for Robust Deepfake Detection." In 2024 International Conference on Communication, Control, and Intelligent Systems (CCIS). IEEE, 2024. https://doi.org/10.1109/ccis63231.2024.10932042.

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Singerhoff, Malte, and Torben Weis. "XTRTimeS — eXplainable Transformer for Robust Time Series Forecasting." In 2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2025. https://doi.org/10.1109/percomworkshops65533.2025.00144.

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Takubo, Yuji, Tommaso Guffanti, Daniele Gammelli, Marco Pavone, and Simone D'Amico. "Towards Robust Spacecraft Trajectory Optimization via Transformers." In 2025 IEEE Aerospace Conference. IEEE, 2025. https://doi.org/10.1109/aero63441.2025.11068406.

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Liu, Yijin, Xianfeng Zeng, Fandong Meng, and Jie Zhou. "BranchNorm: Robustly Scaling Extremely Deep Transformers." In Findings of the Association for Computational Linguistics ACL 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-acl.695.

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Ji, YouChun. "Integrating LSTM and Transformer for Robust Voice Emotion Recognition." In 2025 5th International Conference on Sensors and Information Technology (ICSI). IEEE, 2025. https://doi.org/10.1109/icsi64877.2025.11009609.

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Chiang, Jui-Che, Hou-Ning Hu, Bo-Syuan Hou, et al. "ORFormer: Occlusion-Robust Transformer for Accurate Facial Landmark Detection." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00086.

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Yellapragada, Srikar, Kowshik Thopalli, Vivek Narayanaswamy, et al. "Leveraging Registers in Vision Transformers for Robust Adaptation." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10889287.

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Xu, Jianwei. "Learning with Noisy Annotations by Transformer for Robust Crop Segmentation." In 2024 2nd International Conference on Intelligent Perception and Computer Vision (CIPCV). IEEE, 2024. http://dx.doi.org/10.1109/cipcv61763.2024.00016.

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Chen, Guangyan, Meiling Wang, Yi Yang, Li Yuan, and Yufeng Yue. "Fast and Robust Point Cloud Registration with Tree-based Transformer." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10610004.

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Yu, Hao, Sheng Wu, Liujie Lv, and Yi Su. "A Robust Super-Resolution DoA Estimation Algorithm Using Vision Transformer." In 2024 13th International Conference on Communications, Circuits and Systems (ICCCAS). IEEE, 2024. http://dx.doi.org/10.1109/icccas62034.2024.10652636.

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Reports on the topic "Transformeur robuste"

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Arcia, Diego, Camila Maleronka, Flavia Speyer Carlos, Yara Fonseca Alvez, Jason Hobbs, and Dalve Alexandre Soria Alves. Desenvolvimento orientado ao transporte (DOT) em Teresina: projetos piloto nas zonas centro-norte, leste e sul. Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0013129.

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A publicação "Desenvolvimento Orientado ao Transporte (DOT) em Teresina: Estudo de Caso do Corredor de Ônibus Leste-Oeste" propõe o DOT como estratégia para cidades compactas e sustentáveis, com Teresina como exemplo. Três áreas piloto foram selecionadas e diagnosticadas, com propostas de intervenção para viabilizar o DOT. O estudo recomenda a criação de um marco regulatório específico e prevê diversos benefícios, como aumento da arrecadação pública, investimentos em infraestrutura, desenvolvimento imobiliário e geração de empregos. A implementação do DOT tem potencial para transformar Teresin
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Ramakrishnan, Aravind, Fangyu Liu, Angeli Jayme, and Imad Al-Qadi. Prediction of Pavement Damage under Truck Platoons Utilizing a Combined Finite Element and Artificial Intelligence Model. Illinois Center for Transportation, 2024. https://doi.org/10.36501/0197-9191/24-030.

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For robust pavement design, accurate damage computation is essential, especially for loading scenarios such as truck platoons. Studies have developed a framework to compute pavement distresses as function of lateral position, spacing, and market-penetration level of truck platoons. The established framework uses a robust 3D pavement model, along with the AASHTOWare Mechanistic–Empirical Pavement Design Guidelines (MEPDG) transfer functions to compute pavement distresses. However, transfer functions include high variability and lack physical significance. Therefore, as an improvement to effecti
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Jones, Emily, Beatriz Kira, Anna Sands, and Danilo B. Garrido Alves. The UK and Digital Trade: Which way forward? Blavatnik School of Government, 2021. http://dx.doi.org/10.35489/bsg-wp-2021/038.

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The internet and digital technologies are upending global trade. Industries and supply chains are being transformed, and the movement of data across borders is now central to the operation of the global economy. Provisions in trade agreements address many aspects of the digital economy – from cross-border data flows, to the protection of citizens’ personal data, and the regulation of the internet and new technologies like artificial intelligence and algorithmic decision-making. The UK government has identified digital trade as a priority in its Global Britain strategy and one of the main sourc
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