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User-driven saliency maps for evaluating Region-of-Interest detection.

, , and . WACV, page 389-395. IEEE Computer Society, (2011)

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Investigating Cross-lingual Multi-level Adaptive Networks: The Importance of the Correlation of Source and Target Languages., , , , and . IWSLT, International Workshop on Spoken Language Translation, (2016)Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition., , , and . WACV, page 46-52. IEEE Computer Society, (2013)Domain-invariant I-vector Feature Extraction for PLDA Speaker Verification., , , , and . Odyssey, page 155-161. ISCA, (2018)Short Utterance Variance Modelling and Utterance Partitioning for PLDA Speaker Verification., , , , and . INTERSPEECH, page 1835-1838. ISCA, (2016)Investigating Domain Sensitivity of DNN Embeddings for Speaker Recognition Systems., , , and . ICASSP, page 5811-5815. IEEE, (2019)Jointly Trained Conversion Model With LPCNet for Any-to-One Voice Conversion Using Speaker-Independent Linguistic Features., , , and . IEEE Access, (2022)Investigating Deep Neural Networks for Speaker Diarization in the DIHARD Challenge., , , , and . SLT, page 1029-1035. IEEE, (2018)Automatic region-of-interest detection and prioritisation for visually optimised coding of low bit rate videos., , and . WACV, page 76-82. IEEE Computer Society, (2013)Domain Mismatch Modeling of Out-Domain i-Vectors for PLDA Speaker Verification., , , and . INTERSPEECH, page 1581-1585. ISCA, (2017)Integrating online i-vector extractor with information bottleneck based speaker diarization system., , , and . INTERSPEECH, page 3105-3109. ISCA, (2015)