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Matthew P

As seen in: arXiv, Oxford Academic, Oxford University Press (OUP), U.S. Catholic
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Articles by Matthew P

Computer Science > Machine Learning

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By Matthew P, Justine Raphael H, Vivekjeet Singh
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2510.20759] Controllable Embedding Transformation for Mood-Guided Music Retrieval

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By Matthew P, Juan Pablo
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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[2502.10154] Video Soundtrack Generation by Aligning Emotions and Temporal Boundaries

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By Matthew P
| arXiv
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VEMOCLAP: A video emotion classification web application

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By Matthew P
| arXiv
arXiv:2410.21303 (cs) View PDF HTML (experimental) Comments: Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Multimedia (cs.MM); Image and Video Processing (eess.IV) Cite as: arXiv:2410.21303 [cs.CV] (or arXiv:2410.21303v1 [cs.CV] for this version) https://doi.org/10.48550/arXiv.2410.21303 Submission history From: Serkan Sulun [ view email] [v1] Tue, 22 Oct 2024 10:12:11 UTC (171 KB) Bibliographic Tools Bibliographic...
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[2410.19760] Movie Trailer Genre Classification Using Multimodal Pretrained Features

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By Matthew P
| arXiv
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It’s the Sentiment that Counts: Comparing Sentiment Analysis Tools for Estimating Affective Valence in Dream Reports

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By Matthew P
| Oxford Academic Verified
Accepted manuscripts are PDF versions of the author’s final manuscript, as accepted for publication by the journal but prior to copyediting or typesetting. They can be cited using the author(s), article title, journal title, year of online publication, and DOI. They will be replaced by the final typeset articles, which may therefore contain changes. The DOI will remain the same throughout. This content is only available as a PDF. © The Author(s) 2024.
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[2401.08889] On the Effect of Data-Augmentation on Local Embedding Properties in the Contrastive Learning of Music Audio Representations

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By Matthew P
| arXiv
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[2401.08891] Tempo estimation as fully self-supervised binary classification

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By Matthew P
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Similar but Faster: Manipulation of Tempo in Music Audio Embeddings for Tempo Prediction and Search

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By Matthew P
| arXiv
Happy π Day! Pi Day is finally here – and so is Giving Day for arXiv! Donate today to directly support arXiv initiatives and help keep open science open. Infinite decimals. Infinite new ideas to discover. Infinite reasons to give.
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Serologic Testing of US Blood Donations to Identify Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)-Reactive Antibodies: December 2019-January 2020 | Clinical Infectious Diseases | Oxford Academic

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By Mohammed Ata Ur, Synergy America, So Hee, Matthew P
| Oxford University Press (OUP)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the novel coronavirus disease 2019 (COVID-19), was first identified in Wuhan, China, with notification to the World Health Organization on 31 December 2019, about a cluster of pneumonia cases of unknown etiology and release of the genomic sequence on 10 January 2020 [1]. Subsequent reports have identified a patient with confirmed SARS-CoV-2 hospitalized in Wuhan with symptom onset as early as 1 December 2019 [2].
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