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Pushing the limits of mechanical turk: qualifying the crowd for video geo-location., , , , and . CrowdMM@ACM Multimedia, page 23-28. ACM, (2012)Multi-modal Ensemble Models for Predicting Video Memorability., , , and . CoRR, (2021)The Benchmark as a Research Catalyst: Charting the Progress of Geo-prediction for Social Multimedia., , , , , , , , , and 3 other author(s). Multimodal Location Estimation of Videos and Images, Springer, (2015)Audition for multimedia computing., , , and . Frontiers of Multimedia Research, ACM / Morgan & Claypool, (2018)Appscio: A Software Environment for Semantic Multimedia Analysis., , , and . ICSC, page 456-459. IEEE Computer Society, (2008)Multi-Modal Ensemble Models for Predicting Video Memorability., , , and . MediaEval, volume 2882 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)From Intra-Modal to Inter-Modal Space: Multi-task Learning of Shared Representations for Cross-Modal Retrieval., , , and . BigMM, page 1-10. IEEE, (2019)Deep Layers Beware: Unraveling the Surprising Benefits of JPEG Compression for Image Classification Pre-processing., and . ISM, page 182-185. IEEE, (2023)Team SRI-Sarnoff's AURORA System @ TRECVID 2011., , , , , , , , , and 8 other author(s). TRECVID, National Institute of Standards and Technology (NIST), (2011)Speaker Diarization: A Review of Recent Research., , , , , and . IEEE Trans. Speech Audio Process., 20 (2): 356-370 (2012)