Relevant bibliographies by topics / Multi-modal approach

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

Academic literature on the topic 'Multi-modal approach'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2023

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Journal articles on the topic "Multi-modal approach"

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Winfield, M. J., A. Basden, and I. Cresswell. "Knowledge elicitation using a multi‐modal approach." World Futures 47, no. 1 (September 1996): 93–101. http://dx.doi.org/10.1080/02604027.1996.9972589.

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Bauman, N. James, and Christopher M. Carr. "A Multi-Modal Approach to Trauma Recovery." Psychotherapy Patient 10, no. 3-4 (May 14, 1998): 145–60. http://dx.doi.org/10.1300/j358v10n03_12.

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Huang, Zen‐Kwei, Sheng‐De Wang, and Te‐Son Kuo. "Multi‐modal parameter identification by automata approach." Journal of the Chinese Institute of Engineers 16, no. 5 (July 1993): 603–13. http://dx.doi.org/10.1080/02533839.1993.9677534.

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Fuchs, M., M. Wagner, H. A. Wischmann, Th Köhler, and A. Theißen. "A Multi-Modal Approach to Source Reconstruction." NeuroImage 7, no. 4 (May 1998): S683. http://dx.doi.org/10.1016/s1053-8119(18)31516-7.

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Mailer, Markus. "A Multi-modal Approach for Highway Assessment." Transportation Research Procedia 15 (2016): 113–21. http://dx.doi.org/10.1016/j.trpro.2016.06.010.

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Jennekens-Schinkel, A. "The human memory: A multi-modal approach." Clinical Neurology and Neurosurgery 97, no. 4 (November 1995): 358. http://dx.doi.org/10.1016/0303-8467(95)90014-4.

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Golec, Thomas S. "The multi-modal approach to dental implants." Journal of Oral and Maxillofacial Surgery 49, no. 8 (August 1991): 41–42. http://dx.doi.org/10.1016/0278-2391(91)90541-s.

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Mewaldt, Steven P. "The human memory: A multi-modal approach." Journal of Chemical Neuroanatomy 11, no. 1 (July 1996): 78–79. http://dx.doi.org/10.1016/0891-0618(96)84166-4.

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Kleindienst, Jan, Ladislav Seredi, Pekka Kapanen, and Janne Bergman. "Loosely-coupled approach towards multi-modal browsing." Universal Access in the Information Society 2, no. 2 (June 1, 2003): 173–88. http://dx.doi.org/10.1007/s10209-003-0047-9.

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Kiruthika, M., and S. Sukumaran. "An Improved Multi-Modal Approach for Feature Extraction in Social Media Image Retrieval." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (October 31, 2019): 1447–56. http://dx.doi.org/10.5373/jardcs/v11sp10/20192990.

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Dissertations / Theses on the topic "Multi-modal approach"

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Brookes, Matthew Jon. "A multi-modal approach to functional neuroimaging." Thesis, University of Nottingham, 2005. http://eprints.nottingham.ac.uk/14056/.

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The work undertaken involves the use of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) as separate but complementary non-invasive functional brain imaging modalities. The aim in combining fMRI and MEG is centred around exploitation of the high temporal resolution available in MEG, and the high spatial resolution available in fMRI. However, whilst MEG represents a direct measure of neuronal activity, BOLD fMRI is an indirect measure and this makes the two modalities truly complementary. In both cases, the imaging signals measured are relatively poorly understood and so the fundamental question asked here is: How are the neuromagnetic effects detectable using MEG related to the metabolic effects reflected in the fMRI BOLD response? Initially, a novel technique is introduced for the detection and spatial localisation of neuromagnetic effects in MEG. This technique, based on a beamforming approach to the MEG inverse problem, is shown to yield accurate results both in simulation and using experimental data. The technique introduced is applied to MEG data from a simple experiment involving stimulation of the visual cortex. A number of heterogeneous neuromagnetic effects are shown to be detectable, and furthermore, these effects are shown to be spatially and temporally correlated with the fMRI BOLD response. The limitations to comparing only two measures of brain activity are discussed, and the use of arterial spin labelling (ASL) to make quantitative measurements of physiological parameters supplementing these two initial metrics is introduced. Finally, a novel technique for accurate quantification of arterial cerebral blood volume using ASL is described and shown to produce accurate results. A concluding chapter then speculates on how these aCBV measurements might be combined with those from MEG in order to better understand the fMRI BOLD response.
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Bergvall-Kåreborn, Birgitta. "A multi-modal approach to soft systems methodology /." Luleå : Luleå Univ. of Technology (Luleå tekniska univ.), 2002. http://epubl.luth.se/1402-1544/2002/41.

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Bergvall-Kåreborn, Birgitta. "A multi-modal approach to soft systems methodology." Doctoral thesis, Luleå tekniska universitet, Innovation och Design, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18130.

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The main aim of my research is to explore ways of enriching Soft Systems Methodology by developing intellectual tools that can help designers to conceptualise, create and evaluate different design alternatives. This directs the focus on the methodology’s modelling phase even though some ideas related to analysis also will be presented. In order to realize this objective the study proposes the following supplements. Firstly, a framework of 15 modalities (knowledge areas) is suggested as a supplement to existing analysis techniques, with the aim of helping the analyst identify important aspects that need to be understood in order to identify relevant issues for modelling. Secondly, a concept called qualifying function is proposed as an additional modelling tool for drawing out different perspectives of a particular problem situation, discussing desirable purposes for the design, and for exploring the underlying rationale behind a suggested transformation or a stated Weltanschauung. Thirdly, an expansion of the measures of performance used in SSM modelling, for evaluating conceptual models of possible design alternatives, is suggested. This expansion also builds on the modal framework. Based on both the theoretical and the practical work I have done I conclude that using the modalities as a general framework in analysis, modelling and evaluation, as well as using the concept qualifying function to tease out and clarify relevant transformations and underlying value systems has practical benefits and therefore can be said to enrich Soft Systems Methodology.
Godkänd; 2002; 20060928 (evan)
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Mahoor, Mohammad Hossein. "A Multi-Modal Approach for Face Modeling and Recognition." Scholarly Repository, 2008. http://scholarlyrepository.miami.edu/oa_dissertations/32.

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This dissertation describes a new methodology for multi-modal (2-D + 3-D) face modeling and recognition. There are advantages in using each modality for face recognition. For example, the problems of pose variation and illumination condition, which cannot be resolved easily by using the 2-D data, can be handled by using the 3-D data. However, texture, which is provided by 2-D data, is an important cue that cannot be ignored. Therefore, we use both the 2-D and 3-D modalities for face recognition and fuse the results of face recognition by each modality to boost the overall performance of the system. In this dissertation, we consider two different cases for multi-modal face modeling and recognition. In the first case, the 2-D and 3-D data are registered. In this case we develop a unified graph model called Attributed Relational Graph (ARG) for face modeling and recognition. Based on the ARG model, the 2-D and 3-D data are included in a single model. The developed ARG model consists of nodes, edges, and mutual relations. The nodes of the graph correspond to the landmark points that are extracted by an improved Active Shape Model (ASM) technique. In order to extract the facial landmarks robustly, we improve the Active Shape Model technique by using the color information. Then, at each node of the graph, we calculate the response of a set of log-Gabor filters applied to the facial image texture and shape information (depth values); these features are used to model the local structure of the face at each node of the graph. The edges of the graph are defined based on Delaunay triangulation and a set of mutual relations between the sides of the triangles are defined. The mutual relations boost the final performance of the system. The results of face matching using the 2-D and 3-D attributes and the mutual relations are fused at the score level. In the second case, the 2-D and 3-D data are not registered. This lack of registration could be due to different reasons such as time lapse between the data acquisitions. Therefore, the 2-D and 3-D modalities are modeled independently. For the 3-D modality, we developed a fully automated system for 3-D face modeling and recognition based on ridge images. The problem with shape matching approaches such as Iterative Closest Points (ICP) or Hausdorff distance is the computational complexity. We model the face by 3-D binary ridge images and use them for matching. In order to match the ridge points (either using the ICP or the Hausdorff distance), we extract three facial landmark points: namely, the two inner corners of the eyes and the tip of the nose, on the face surface using the Gaussian curvature. These three points are used for initial alignment of the constructed ridge images. As a result of using ridge points, which are just a fraction of the total points on the surface of the face, the computational complexity of the matching is reduced by two orders of magnitude. For the 2-D modality, we model the face using an Attributed Relational Graph. The results of the 2-D and 3-D matching are fused at the score level. There are various techniques to fuse the 2-D and 3-D modalities. In this dissertation, we fuse the matching results at the score level to enhance the overall performance of our face recognition system. We compare the Dempster-Shafer theory of evidence and the weighted sum rule for fusion. We evaluate the performance of the above techniques for multi-modal face recognition on various databases such as Gavab range database, FRGC (Face Recognition Grand Challenge) V2.0, and the University of Miami face database.
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Langley, Dawn. "An explosive force : A multi-level, multi-modal approach to organisational learning." Thesis, University of Surrey, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.527014.

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Knight, Dawn. "A multi-modal corpus approach to the analysis of backchanneling behaviour." Thesis, University of Nottingham, 2009. http://eprints.nottingham.ac.uk/10786/.

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Current methodologies in corpus linguistics have revolutionised the way we look at language. They allow us to make objective observations about written and spoken language in use. However, most corpora are limited in scope because they are unable to capture language and communication beyond the word. This is problematic given that interaction is in fact multi-modal, as meaning is constructed through the interplay of text, gesture and prosody; a combination of verbal and non-verbal characteristics. This thesis outlines, then utilises, a multi-modal approach to corpus linguistics, and examines how such can be used to facilitate our explorations of backchanneling phenomena in conversation, such as gestural and verbal signals of active listenership. Backchannels have been seen as being highly conventionalised, they differ considerably in form, function, interlocutor and location (in context and co-text). Therefore their relevance at any given time in a given conversation is highly conditional. The thesis provides an in-depth investigation of the use of, and the relationship between, spoken and non-verbal forms of this behaviour, focusing on a particular sub-set of gestural forms: head nods. This investigation is undertaken by analysing the patterned use of specific forms and functions of backchannels within and across sentence boundaries, as evidenced in a five-hour sub-corpus of dyadic multi-modal conversational episodes, taken from the Nottingham Multi-Modal Corpus (NMMC). The results from this investigation reveal 22 key findings regarding the collaborative and cooperative nature of backchannels, which function to both support and extend what is already known about such behaviours. Using these findings, the thesis presents an adapted pragmatic-functional linguistic coding matrix for the classification and examination of backchanneling phenomena. This fuses the different, dynamic properties of spoken and non-verbal forms of this behaviour into a single, integrated conceptual model, in order to provide the foundations, a theoretical point-of-entry, for future research of this nature.
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Zhou, Shi Huang. "Operational modal decomposition approach for MDOF structures using multi-channel response measurements." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3950681.

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Tjondronegoro, Dian W., and mikewood@deakin edu au. "Content-based video indexing for sports applications using integrated multi-modal approach." Deakin University. School of Information Technology, 2005. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20051110.122059.

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This thesis presents a research work based on an integrated multi-modal approach for sports video indexing and retrieval. By combining specific features extractable from multiple (audio-visual) modalities, generic structure and specific events can be detected and classified. During browsing and retrieval, users will benefit from the integration of high-level semantic and some descriptive mid-level features such as whistle and close-up view of player(s). The main objective is to contribute to the three major components of sports video indexing systems. The first component is a set of powerful techniques to extract audio-visual features and semantic contents automatically. The main purposes are to reduce manual annotations and to summarize the lengthy contents into a compact, meaningful and more enjoyable presentation. The second component is an expressive and flexible indexing technique that supports gradual index construction. Indexing scheme is essential to determine the methods by which users can access a video database. The third and last component is a query language that can generate dynamic video summaries for smart browsing and support user-oriented retrievals.
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Zaverucha, Gerson. "A nonmonotonic multi-agent logic of belief : a Modal Defeasible Relevant approach." Thesis, Imperial College London, 1990. http://hdl.handle.net/10044/1/46629.

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Suthana, Nanthia Ananda. "Investigating human medical temporal representations of episodic information a multi-modal approach /." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1905692921&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Books on the topic "Multi-modal approach"

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A multi-modal approach to creative art therapy. London: J. Kingsley, 1994.

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Chambers, Mary-Lynn. Pedagogy and Practice: A Multi-modal Approach for a Multi-ethnic Online Classroom. Common Ground Research Networks, 2016. http://dx.doi.org/10.18848/978-1-61229-831-3/cgp.

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Henderson, Renee. Language development in young handicapped children: A makaton multi-modal approach. 1990.

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Wu, Min, Lu Yang, Dong-Hyun Kim, Changqiang Wu, and Peng Mi, eds. Bottom-Up Approach: a Route for Effective Multi-modal Imaging of Tumors. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88974-453-4.

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A Decomposition Approach for the Multi-Modal, Resource-Constrained, Multi-Project Scheduling Problem with Generalized Precedence and Expediting Resources. Storming Media, 2001.

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Planning Coverage of Points of Interest via Multiple Imaging Surveillance Assets: A Multi-Modal Approach. Storming Media, 2003.

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Bradley, Ramsey. Mental Health/Substance Abuse Assessment Guide: A Comprehensive, Multi-Modal Approach to Screening and Identifying Client Needs. Independently Published, 2018.

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Young, Catherine A. M-MAT Multi-Modal Attachment Therapy: An Integrated Whole-Brain Approach to Attachment Injuries in Children and Families. Granite Swan Press, 2021.

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Changes in Pilot Control Behaviour across Stewart Platform Motion Systems. Berlin, Germany: Logos-Verlag Berlin, 2012.

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Whiting, Rebecca, Helen Roby, Gillian Symon, and Petros Chamakiotis. Participant-led video diaries. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198796978.003.0010.

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Rebecca Whiting, Helen Roby, Gillian Symon, and Petros Chamakiotis develop an unconventional research design using video methods, asking participants to produce their own video diaries, a process which is then followed by narrative interviews. This approach generates multi-modal data: audio, visual, and textual, and involves adopting a qualitative perspective, and a social constructionist epistemology. This participant-led research design allows researchers to investigate a range of issues that are not often recalled in interviews or surveys, by capturing naturally occurring, real-time events and activities, and micro-interactions including non-verbal behaviours. Although video methods are used in other disciplines, they are rare in organizational research. The approach is illustrated by a study which explored how digital technologies affect our ability to manage switches across work-life boundaries. Analysis of participants’ video diaries illustrates the theoretical and reflexive insights that can be gained from this method. The problems and pitfalls encountered in this study are also considered.
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Book chapters on the topic "Multi-modal approach"

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Laitinen, Minna, Maire Ratasvuori, and Toni-Karri Pakarinen. "The Multi-modal Approach to Metastatic Disease." In European Instructional Lectures, 35–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27293-6_4.

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Knott, Camilla C., Alexandra Geyer, Jason Sidman, and Emily Wiese. "Multi-Modal Measurement Approach to Team Cohesion." In Foundations of Augmented Cognition. Directing the Future of Adaptive Systems, 318–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21852-1_38.

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MariAnne Karlsson, I. C., Fredrick Ekman, and Mikael Johansson. "Designing Multi-modal Interaction – A Basic Operations Approach." In Advances in Intelligent Systems and Computing, 43–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96059-3_5.

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Goldhahn, Eila, Soili Hämäläinen, and Leena Rouhiainen. "Collaborative choreography: experimenting with a multi-modal approach." In Reflections on Authentic Movement, 138–45. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003222309-14.

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García-Vega, Manuel, Miguel A. García-Cumbreras, L. Alfonso Ureña-López, José M. Perea-Ortega, F. Javier Ariza-López, Oscar Ferrández, Antonio Toral, et al. "R2D2 at GeoCLEF 2006: A Combined Approach." In Evaluation of Multilingual and Multi-modal Information Retrieval, 918–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74999-8_117.

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Song, Yunfeng, Xiaochao Fan, Yong Yang, Ge Ren, and Weiming Pan. "A Cross-Modal Attention and Multi-task Learning Based Approach for Multi-modal Sentiment Analysis." In Lecture Notes in Electrical Engineering, 159–66. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9423-3_20.

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Koo, T. John, Judy Liebman, Cedric Ma, and S. Shankar Sastry. "Hierarchical Approach for Design of Multi-vehicle Multi-modal Embedded Software." In Embedded Software, 344–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45449-7_24.

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Vilares, Jesús, Michael P. Oakes, and John I. Tait. "A First Approach to CLIR Using Character N-Grams Alignment." In Evaluation of Multilingual and Multi-modal Information Retrieval, 111–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74999-8_15.

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Bos, Johan, and Malvina Nissim. "Answer Translation: An Alternative Approach to Cross-Lingual Question Answering." In Evaluation of Multilingual and Multi-modal Information Retrieval, 290–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74999-8_36.

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Harders, Matthias, and Gábor Székely. "A Multi-modal Approach to Segmentation of Tubular Structures." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001, 1180–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45468-3_153.

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Conference papers on the topic "Multi-modal approach"

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Siddharth, Tzyy-Ping Jung, and Terrence J. Sejnowski. "Multi-modal Approach for Affective Computing." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8512320.

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Zhang, Yun, Gangyi Jiang, Wenjuan Yi, Mei Yu, Zhidi Jiang, and Yong Kim. "An Approach to Multi-Modal Multi-View Video Coding." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.345621.

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Yu, Haicong, and Feng Lu. "Advanced multi-modal routing approach for pedestrians." In 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet). IEEE, 2012. http://dx.doi.org/10.1109/cecnet.2012.6201641.

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Méndez, Carlos Andrés, Paul Summers, and Gloria Menegaz. "A multi-view approach to multi-modal MRI cluster ensembles." In SPIE Medical Imaging, edited by Sebastien Ourselin and Martin A. Styner. SPIE, 2014. http://dx.doi.org/10.1117/12.2042327.

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Ferradans, Sira, Marcelo Bertalmío, Edoardo Provenzi, and Vicent Caselles. "A Multi-Modal Approach to Perceptual Tone Mapping." In 2009 Conference for Visual Media Production (CVMP). IEEE, 2009. http://dx.doi.org/10.1109/cvmp.2009.16.

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Moamen, Ahmed Abdel, and Nadeem Jamali. "ModeSens: an approach for multi-modal mobile sensing." In SPLASH '15: Conference on Systems, Programming, Languages, and Applications: Software for Humanity. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2814189.2817271.

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Harira, P., and Vivek Ramanath. "A Multi-Modal Approach to Natural Gas Transportation." In ICSOT India 2015. RINA, 2015. http://dx.doi.org/10.3940/rina.icsotin15.2015.03.

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Steele, Alec M., Mehrdad Nourani, Melinda M. Bopp, Tanya S. Taylor, and Dennis H. Sullivan. "A Multi-Modal Approach to Patient Activity Monitoring." In 2020 IEEE International Conference on Healthcare Informatics (ICHI). IEEE, 2020. http://dx.doi.org/10.1109/ichi48887.2020.9374362.

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Srimal, Arjuna S., and A. G. Buddhika P. Jayasekara. "A multi-modal approach for enhancing object placement." In 2017 6th National Conference on Technology and Management (NCTM). IEEE, 2017. http://dx.doi.org/10.1109/nctm.2017.7872821.

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Gibilisco, Hannah, Michael Laubenberger, Valerii Spiridonov, Jacob Belga, Jason O. Hallstrom, and Paul R. Peluso. "A Multi-Modal Approach to Sensing Human Emotion." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622451.

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Reports on the topic "Multi-modal approach"

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Zhu, Zhigang, and Harvey E. Rhody. A System Approach to Adaptive Multi-Modal Sensor Designs. Fort Belvoir, VA: Defense Technical Information Center, February 2010. http://dx.doi.org/10.21236/ada528562.

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Sakidja, Ridwan, Wai-Yim Ching, and Caizhi Zhou. Multi-modal Approach to Modeling Creep Deformation in Nickel-base Superalloy. Office of Scientific and Technical Information (OSTI), June 2022. http://dx.doi.org/10.2172/1874338.

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