Daniele Barchiesi
Artificial Intelligence · 2014
A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 8 citations into it
- Signal Processing — 8 citations into it; #4,415 of 7,572 by trust here, #4,750 by citations
- Computer Vision and Pattern Recognition — 5 citations into it; #13,396 of 21,575 by trust here, #15,955 by citations
Whom Daniele Barchiesi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert E. Schapire
- Jean-Julien Aucouturier
- Lie Lu
- Selina M. Chu
- C.-C. Jay Kuo
- Antti J. Eronen
- François Pachet
- HongJiang Zhang
- Shrikanth S. Narayanan
Who trusts Daniele Barchiesi overall
- Annamaria Mesaros
- Toni Heittola
- Dan Stowell
- Karol J. Piczak
- Tuomas Virtanen
- Emmanouil Benetos
- Eduardo Fonseca
- Peter Foster
- Dimitrios Giannoulis
Papers from Daniele Barchiesi's perspective
Ordered by how strongly the researchers Daniele Barchiesi trusts endorse each paper. Same corpus, a different order for every researcher.
- Audio-based context recognition (IEEE Transactions on Audio, Speech, and Language Processing)
- Fundamentals of speech recognition
- Audio content analysis for online audiovisual data segmentation and classification (IEEE Transactions on Speech and Audio Processing)
- The Boosting Approach to Machine Learning An Overview
- The PASCAL CHiME speech separation and recognition challenge
- Environmental Sound Recognition With Time–Frequency Audio Features (IEEE Transactions on Audio, Speech, and Language Processing)
- Support vector machines versus fast scoring in the low-dimensional total variability space for speaker verification
- Computational Auditory Scene Analysis: Principles, Algorithms, and Applications (IEEE Trans. Neural Networks)
- Reproducible research in signal processing (IEEE Signal Processing Magazine)
- The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings
Their papers
- Acoustic Scene Classification: Classifying environments from the sounds they produce (2014) — 434 citations