Alexander Schindler

Dipl.-Ing. Dr. techn. / Bakk.techn.

Institute of Software Technology and Interactive Systems
Vienna University of Technology
Faculty of Informatics
Institute of Information Systems Engineering
Information & Software Engineering

Office: Room HE 01 46
Hours: by appointment
email: schindler@ifs.tuwien.ac.at

Favoritenstraße 9-11/188
A-1040 Wien
Austria

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AIT Austrian Institute of Technology GmbH
Information Management
Center for Digital Safety & Security
email: alexander.schindler@ait.ac.at

Giefinggasse 4
A-1210 Vienna
Austria

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Team Member

News


  • Starting a new lecture on "Special Topics in Artificial Intelligence" at St. Pölten University of Applied Sciences, WS21/22
  • Looking for MSc students: [Audio] audio tampering detection, audio captioning, audio event detection. [NLP] NLP in massive content collections, narrative extraction, detection of toxic content (e.g. hate-speech), trend analysis. [Multi-Modal] combining audio and text, audio and video, etc.
  • New course in WS 2018/19: Intelligent Audio and Music Analysis (VU, 3h, 4.5 ECTS)

Background

Awards

  • Our joint NLP team (AIT & FH St. Pölten) placed 3rd out of 33 teams in Task 1 of the sEXism Identification in Social neTworks (EXIST) challenge 2021.
  • Best Student Paper Award "Alexander Schindler and Peter Knees. Multi-Task Music Representation Learning from Multi-Label Embeddings" at the International Conference on Content-Based Multimedia Indexing (CBMI2019). Dublin, Ireland, 4-6 Sept 2019
  • Winner of the Domestic Audio Tagging task of the DCASE 2016 challenge (Team Thomas Lidy and Alexander Schindler)
  • Winning contributions of the Classical Composer Identification, Genre Classification (Latin), Mood Classification, KPOP genre classification tasks of the MIREX 2016 campaign (Team Thomas Lidy and Alexander Schindler)

Research Interests


Academic Research

  • Audio-Visual Analysis of Music
    • Color, Motion, Aesthetics
  • Music Video Information Retrieval (MIR)
    • Artist Identification
    • Genre Classification
    • Mood/Affect Recognition
    • Similarity Retrieval
    • Music Video Benchmarking
  • Music Information Retrieval (MIR)
    • Similarity Retrieval
    • Music Benchmarking
    • Automatic Playlist Generation

Non-Academic Research

  • Music Information Retrieval
    • Score Following
    • Audio-Midi Synchronization
  • Image Processing
    • Object Detection
    • Scene Recognition
    • High Performance Image Processing
  • Digital Preservation
    • Document Image Processing
    • Near Duplicate Detection in Image Collections

Teaching


Supervision of student projects

Supervision of praktika, bachelor theses, etc. Topics in the field of Music Information Retrieval. See Topics for practical works and theses in the Music Information Retrieval domain

Lectures

Scientific Services


Program Chair / Organizer of Scientific Events


Service on Program Committees

Program Committee Member of the International Society for Music Information Retrieval Conference

Program Committee / Technical Program Committee Member


Reviewer

Journals
  • ACM Transactions on Interactive Intelligent Systems (TIIS)
  • ACM Transactions on Intelligent Systems and Applications (TIST)
  • International Journal of Multimedia Information Retrieval
  • Transaction of the International Society for Music Information Retrieval (TISMIR)
  • International Journal of Computing and Digital Systems'20 (IJCDS-2020)
  • Multimedia Tools and Applications (MTAP)
  • Applied Sciences (ISSN 2076-3417; CODEN: ASPCC7)
  • Energies (ISSN 1996-1073; CODEN: ENERGA)
  • Sensors (ISSN 1424-8220; CODEN: SENSC9)
Conferences and Workshops
  • ISMIR 2012 - 2020
  • European Association for Signal Processing 2020
  • ACM Multimedia 2019, 2020
  • Semantics 2018, 2020
  • ICASSP 2020
  • Detection and Classification of Acoustic Scenes and Events (DCASE), 2018 - 2020
  • Digital Libraries Conference
  • European Conference on Information Retrieval

Projects and Activities

Projects

[Defalsif-AI - 10/2020 - 09/2022]
[FFG KIRAS, Work Package Lead]. defalsif-AI addresses the problem of disinformation in the context of an attack on democracy and the public trust in its institutions. The official stakeholders BKA, BMLV and BMEIA, are concerned about potential external attacks on the Austrian democratic process. At the same time, the Austrian Broadcasting Corporation (ORF) and the Austria Press Agency (APA) are concerned about fulfilling their crucial roles as journalistic institutions. Based on these stakeholder requirements, the project focuses on research in the areas of audio-visual media forensics, text analysis and the multimodal fusion of these with the support of Artificial Intelligence (AI) and Machine Learning methods. A principal focus of this research will be in enhancing the comprehensibility and interpretability of the results for non-experts in the forensic/technical field.
[AMMONIS - 10/2020 - 09/2022]
[FFG FORTE, Work Package Lead]. In the AMMONIS project, services are being developed for the linked analysis of audio and text data using heterogeneous data sources. These services enable the classification and linking of audio events with text information that is related spatially, temporally or thematically. The goal is to use these services to detect contradictory - or complementary - representations in the different news channels, thus enabling improved monitoring and early detection.
[Study: Disinformation - Threads and Resilience Options - 01/2020 - 12/2020]
[Contract Research, Project Lead] This comprehensive study researches and evaluates a broad perspective of current threads through online disinformation, state-of-the-art approaches to create as well as identify disinformation on the web, and options to counter disinformation on various scales.
[COPKIT - 2018 - 2021]
[H2020 Project, Researcher]. The COPKIT project focuses on the problem of analysing, investigating, mitigating and preventing the use of new information and communication technologies by organised crime and terrorist groups. For this purpose, COPKIT proposes an intelligence-led Early Warning (EW) / Early Action (EA) system for both strategic and operational levels. The project duration is 36 months (from 2018 to 2021).
[VICTORIA - 05/2017 - 11/2020]
[H2020 Project, Task Lead]. This projects develops a framework for state-of-the-art media forensic tools to assist Law Enforcement Agencies (LEA) in post-terrorist-attack scenarios. VICTORIA will deliver a Video Analysis Platform (VAP) with a scalable architecture based on big data technologies, feature new user interface paradigms allowing complex semantic investigation queries and 4D crime scene reconstruction, be adaptable to specific user needs, and be future proof thanks to an open analytic plug-in feature, based on standardized interfaces and open to third party suppliers.
[Speech2Text - 03/2019 - 02/2020]
[FFG Innovationsscheck, Principal Investigator] The aim of this project is to build speech recognition models for the Austrian idiom based on open source speech recognition frameworks and state-of-the-art approaches. Tasks of this project include annotating recorded speech as well as training and evaluating acoustic and language models.
[SpeechRec - 02/2019 - 01/2020]
[FFG Innovationsscheck, Principal Investigator] The aim of this project is to automate the task of consulting seminar transcription and sentence categorization through state-of-the-art speech recognition and natural language processing approaches.
[FLORIDA - 11/2016 - 02/2019]
[FFG KIRAS, Workpackage Lead] With the help of FLORIDA, a flexible, semi-automated system is to be created which will support the authorities responsible for public security administration, such as the Federal Office for the Protection of the Constitution and Counter-Terrorism (BM.I.BVT), in investigating, providing evidence and clarifying the situation following attacks. By using state-of-the-art technologies, the system will noticeably improve the quality of work and working conditions for the people employed in this field, as it will simplify the research, processing and analysis of extremely extensive and heterogeneous inventories of audio and video data. The main developments in the project to make this possible are The creation of a scalable open-source platform for forensic video analysis on a large scale; the definition of interfaces to allow different (video) programs to access them.
[Europeana Sounds - 02/2014 - 01/2017]
[EU Europeana, Researcher] The Europeana Sounds project became the domain aggregator for audio and audio-related material. Europeana Sounds is hosted by the British Library, supported by the Europeana Sounds Task Force. Europeana Music, which was developed as part of the Europeana Sounds project, is also curated by the British Library. Europeana Sounds therefore also aggregates collections with music-related content, such as music manuscripts, printed music, photographs of musicians, etc. Europeana Sounds has over 530,000 records on Europeana, corresponding to around 618,000 audio recordings and 312,000 audio-related objects. Currently 20 archives contribute to Europeana through Europeana Sounds.
[MusicBricks - 01/2015 - 06/2016]
[H2020 Project, Workpackage Lead] The goal of the European project MusicBricks is to facilitate the transfer of new musical technologies from major European research centers specialized in the domain to small digital creation companies. The project involves the creation of programming interfaces, of graphic and tangible user interfaces, the development of an ecosystem based on events during Music Tech Fest and in selected technology incubators to prepare access to the market.
[Scape - 02/2011 - 09/2014]
[EU FP7 Project, Researcher] The SCAPE project developed scalable services for planning and execution of institutional preservation strategies on an open source platform that orchestrates semi-automated workflows for large-scale, heterogeneous collections of complex digital objects. SCAPE developed infrastructure and tools for scalable preservation actions, provided a framework for automated, quality-assured preservation workflows, and integrated these components with a policy-based preservation planning and watch system. These project results were validated within four large-scale Testbeds from diverse application areas. SCAPE has made a significant impact on the community and practice of digital preservation.
[CHORUS+ - 01/2010 - 12/2012]
[EU FP7 Project, Researcher] The SCAPE project developed scalable services for planning and execution of institutional preservation strategies on an open source platform that orchestrates semi-automated workflows for large-scale, heterogeneous collections of complex digital objects. SCAPE developed infrastructure and tools for scalable preservation actions, provided a framework for automated, quality-assured preservation workflows, and integrated these components with a policy-based preservation planning and watch system. These project results were validated within four large-scale Testbeds from diverse application areas. SCAPE has made a significant impact on the community and practice of digital preservation.

Publications

[SSSN21]
Boeck Jaqueline, Liakhovets Daria, Mina Schuetz, Armin Kirchknopf, Djordje Slijepčević, Matthias Zeppelzauer, Alexander Schindler. AIT_FHSTP at GermEval 2021: Automatic Fact Claiming Detection with Multilingual Transformer Models. In Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments : 17th Conference on Natural Language Processing KONVENS 2021. Düsseldorf, 2021
[SSSN21]
Lam Pham, Hieu Tang, Anahid Jalali, Alexander Schindler, Ross King. A Low-Compexity Deep Learning Framework For Acoustic Scene Classification. International Data Science Conference (iDSC), Vienna, Austria, October 20-21, 2021
[SSSN21]
Lam Pham, Dat Ngo, Alexander Schindler, Ross King. A Deep Neural Network And Triplet Loss For Detecting Anomaly Of Respiratory Sounds. DAGA 2021 - 47TH ANNUAL ACOUSTICS CONFERENCE. Vienna, Austria, August 15-18, 2021
[SSSN21]
Lam Pham, Huy Phan, Alexander Schindler, Ross King, Alfred Mertins, Ian McLoughlin. Inception-Based Network and Multi-Spectrogram Ensemble Applied To Predict Respiratory Anomalies and Lung Diseases. 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society October 31 – November 4, 2021
[SSSN21]
Lam Pham, Dat Ngo, Alexander Schindler, Ross King. A Deep Neural Network And Triplet Loss For Detecting Anomaly Of Respiratory Sounds. DAGA 2021 - 47TH ANNUAL ACOUSTICS CONFERENCE. Vienna, Austria, August 15-18, 2021
[JSH20]
Lam Pham, Alexander Schindler, Hieu Tang and Truong Hoang. DCASE 2021 Task 1A: Technique Report . DCASE2021 Challenge (Report). July, 2021. [pdf]
[JSH20]
Lam Pham, Alexander Schindler, Mina Schutz, Jasmin Lampert and Ross King. DCASE 2021 Task 1B: Technique Report. DCASE2021 Challenge (Report). July, 2021. [pdf]
[JSH20]
Lam Pham, Anahid Jalali, Olivia Dinica, and Alexander Schindler. DCASE Challenge 2021: Unsupervised Anomalous Sound Detection of Machinery with LeNet Architecture. DCASE2021 Challenge (Report). July, 2021. [pdf]
[SSSN21]
Mina Schuetz, Alexander Schindler, Melanie Siegel. Disinformation Detection, An Explainable Transfer Learning Approach. CODE 2021 science track, Munich, Germany, July 20-22, 2021. [pdf]
[SSSN21]
Mina Schuetz, Boeck Jaqueline, Liakhovets Daria, Slijepčević Djordje, Kirchknopf Armin, Hecht Manuel, Bogensperger Johannes, Sven Schlarb, Alexander Schindler, Zeppelzauer Matthias. Automatic Sexism Detection with Multilingual Transformer Models - AIT_FHSTP@EXIST2021. Technical Report. EXIST Challenge 2021. [pdf]
[SSSN21]
Mina Schuetz, Alexander Schindler, Melanie Siegel, Kawa Nazemi. Automatic Fake News Detection with Pre-Trained Transformer Models. 3rd International Workshop on Research & Innovation for Secure Societies - RISS 2020, Milan, Italy, January 10-15, 2021. [pdf]
[CWG20]
Carmina Coronel, Christoph Wiesmeyr, Heinrich Garn, Bernhard Kohn, Anahid Naghibzadeh-Jalali, Alexander Schindler, Markus Wimmer, Magdalena Mandl, Martin Glos, Thomas Penzel, Gerhard Kloesch, Andrijana Stefanic-Kejik, Marion Boeck, Eugenijus Kaniusas, Stefan Seidel. Comparison of PSG signals and Respiratory Movement Signal via 3D Camera in Detecting Sleep Respiratory Events by LSTM Models. APSIPA ASC 2020. [pdf]
[JSH20]
Anahid Jalali, Alexander Schindler and Bernhard Haslhofer. DCASE Challenge 2020: Unsupervised Anomalous Sound Detection of Machinery with Deep Autoencoders. DCASE2020 Challenge (Report). July, 2020. [pdf]
[JSHR20]
Anahid Jalali, Alexander Schindler, Bernhard Haslhofer, Andreas Rauber. Machine Learning Interpretability Techniques for Outage Prediction: A Comparative Study. In Proceedings of the 5th European Confernece of the Prognostics and Health Management Society (PHME2020). July 27-31, 2020. [pdf]
[SLJBGK20]
Alexander Schindler, Andrew Lindley, Anahid Jalali, Martin Boyer, Sergiu Gordea and Ross King. Multi-Modal Video Forensic Platform for Investigating Post-Terrorist Attack Scenarios. In Proceedings of the 11th ACM Multimedia Systems Conference (MMSys2020), June 06-11, 2020, Istanbul, Turkey. [pdf]
[ASK20a]
Alexander Schindler, Sergiu Gordea and Peter Knees. Unsupervised Cross-Modal Audio Representation Learning from Unstructured Multilingual Text. In Proceedings of the 35th ACM/SIGAPP Symposium On Applied Computing (SAC2020), March 30-April 3, 2020, Brno, Czech Republic. [pdf]
[JHS19]
Alexander Schindler, Sergiu Gordea and Peter Knees. Unsupervised Cross-Modal Audio Representation Learning from Unstructured Multilingual Text. In Proceedings of the 35th ACM/SIGAPP Symposium On Applied Computing (SAC2020), March 30-April 3, 2020, Brno, Czech Republic. [pdf]
[AS19]
Alexander Schindler. Multi-Modal Music Information Retrieval: Augmenting Audio-Analysis with Visual Computing for Improved Music Video Analysis. PhD-thesis. TU-Wien. October, 2019 [pdf ]
[SK19]
Alexander Schindler and Peter Knees. Multi-Task Music Representation Learning from Multi-Label Embeddings. In Proceedings of the International Conference on Content-Based Multimedia Indexing (CBMI2019). Dublin, Ireland, 4-6 Sept 2019. [pdf]
[SR18]
Alexander Schindler and Andreas Rauber. On the unsolved problem of Shot Boundary Detection for Music Videos. In Proceedings of the 25th International Conference on MultiMedia Modeling (MMM2019), January 8-11, 2019, in Thessaloniki, Greece. [pdf]
[SLSBP18]
Alexander Schindler, Andrew Lindley, David Schreiber, Martin Boyer and Thomas Philipp. Large Scale Audio-Visual Video Analytics Platform for Forensic Investigations of Terroristic Attacks. In Proceedings of the 25th International Conference on MultiMedia Modeling (MMM2019), January 8-11, 2019, in Thessaloniki, Greece. [pdf]
[JHS19]
Anahid Jalali, Clemens Heistracher, Alexander Schindler, Bernhard Haslhofer, Tanja Nemeth, Robert Glawar, Wilfried Sihn, Peter De Boer. Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning. In Proceedings of the IEEE International Conference on Prognostics and Health Management (PHM2019), June 17-19, 2019, in San Francisco, USA. [pdf]
[JSH19]
Anahid N Jalali, Alexander Schindler, Bernhard Haslhofer. Understandable Deep Neural Networks for Predictive Maintenance in the Manufacturing Industry In ERCIM News, Number 116, Jan 2019.
[SLSBP18]
Nemeth, Tanja, Fazel Ansari, Wilfried Sihn, Bernhard Haslhofer, and Alexander Schindler. PriMa-X: A reference model for realizing prescriptive maintenance and assessing its maturity enhanced by machine learning. Procedia CIRP 72 (2018): 1039-1044. [pdf]
[SLSBP18]
Alexander Schindler, Thomas Lidy and Sebastian Boeck. Deep Learning for MIR Tutorial. Tutorial held at the 19th International Society for Music Information Retrieval Conference, ISMIR 2018, Paris, France, September 23-27, 2018. 2018 [arXiv]
[SS18]
Alexander Schindler and Sven Schlarb. Contextualised Conversational Systems. In ERCIM News, Number 114, July 2018.
[SLR17a]
Alexander Schindler, Thomas Lidy and Andreas Rauber. Multi-Temporal Resolution Convolutional Neural Networks for Acoustic Scene Classification. In Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), November 2017. [pdf ]
[SLR17b]
Alexander Schindler, Thomas Lidy and Andreas Rauber. Multi-Temporal Resolution Convolutional Neural Networks for the DCASE Acoustic Scene Classification Task. Technical report, DCASE2017 Challenge, November 2017. [pdf ]
[FSLR17]
Botond Fazekas, Alexander Schindler, Thomas Lidy, Andreas Rauber. A multi-modal deep neural network approach to bird-song identification. LifeCLEF 2017 working notes, Dublin, Ireland [pdf ]
[SLKH17]
Alexander Schindler, Thomas Lidy, Stefan Karner and Matthias Hecker. Fashion and Apparel Classification using Convolutional Neural Networks. In Proceedings of the 9th Forum Media Technology (FMT2017), St. Poelten, Austria, October 29, 2017. [pdf ]
[SR16]
Alexander Schindler and Andreas Rauber. Harnessing Music related Visual Stereotypes for Music Information Retrieval. ACM Transactions on Intelligent Systems and Technology (TIST) 8.2 (2016): 20 [pdf ]
[SLR16]
Alexander Schindler, Thomas Lidy, and Andreas Rauber. Comparing shallow versus deep neural network architectures for automatic music genre classification. In Proceedings of the 9th Forum Media Technology (FMT2016), St. Poelten, Austria, November 23 - November 24 2016. [ bib ]
[SGvB16]
Alexander Schindler, Sergiu Gordea, and Harry van Biessum. The europeana sounds music information retrieval pilot. In Proceedings of the International Conference on Cultural Heritage (EuroMed2016), Lecture Notes in Computer Science, Cyprus, October 31 - November 5 2016. Springer. [ bib | pdf ]
[LS16a]
Thomas Lidy and Alexander Schindler. CQT-based convolutional neural networks for audio scene classification. In Proceedings of the Detection and Classification of Acoustic Scenes and Events 2016 Workshop (DCASE2016), pages 60--64, September 2016. [ bib | pdf ]
[LS16b]
Thomas Lidy and Alexander Schindler. CQT-based convolutional neural networks for audio scene classification and domestic audio tagging. Technical report, DCASE2016 Challenge, September 2016. [ bib | pdf ]
[LS16c]
Thomas Lidy and Alexander Schindler. Parallel convolutional neural networks for music genre and mood classification. Technical report, Music Information Retrieval Evaluation eXchange (MIREX 2016), August 2016. [ bib | pdf ]
[LS15]
Thomas Lidy, Alexander Schindler and Michela Magas. MusicBricks: Connecting Digital Creators to the Internet of Music Things. In ERCIM News, Number 101, April 2015. [ bib| pdf ]
[SR15]
Alexander Schindler and Andreas Rauber. An audio-visual approach to music genre classification through affective color features. In Proceedings of the 37th European Conference on Information Retrieval (ECIR'15), Vienna, Austria, March 29 - April 02 2015. [ bib| pdf ]
[LS15]
Thomas Lidy and Alexander Schindler. Klingende bausteine für die industrie. OCG Journal, (40):17--18, 2015. [ bib | .pdf ]
[Sch14]
Alexander Schindler. A picture is worth a thousand songs: Exploring visual aspects of music. In Proceedings of the 1st International Digital Libraries for Musicology workshop (DLfM 2014), London, UK, September 12 2014. [ bib| pdf ]
[GSHM14]
Roman Graf, Alexander Schindler, and Reinhold Huber-Mörk. A fuzzy logic based expert system for quality assurance of document image collections. In International Journal of Arts & Sciences IJAS 2014 to appear, Valetta, Malta, March 2-6 2014. [ bib| pdf ]
[GHMSS13]
Roman Graf, Reinhold Huber-Mörk, Alexander Schindler, and Sven Schlarb. Duplicate detection approaches for quality assurance of document image collections. In Proceedings of the International ACM Conference on Management of Emergent Digital EcoSystems (MEDES'13) to appear, Neumünster Abbey, Luxembourg, October 28-31 2013. [ bib| pdf ]
[SHM13]
Alexander Schindler and Reinhold Huber-Moerk. Towards objective quality assessment in digital image collections. In Proceedings of the 2nd Workshop on Open Research Challenges in Digital Preservation (ORC'13) to appear, Lisbon, Portugal, September 6 2013. [ bib| pdf ]
[SR13]
Alexander Schindler and Andreas Rauber. A music video information retrieval approach to artist identification. In Proceedings of the 10th International Symposium on Computer Music Multidisciplinary Research (CMMR2013) to appear, Marseille, France, October 14-18 2013. [ bib| pdf ]
[HMS13a]
Reinhold Huber-Moerk and Alexander Schindler. Automatic classification of defect page content in scanned document collections. In Proceedings of the 8th International Symposium on Image and Signal Processing and Analysis (ISPA 2013) to appear, Trieste, Italy, September 4-6 2013. [ bib ]
[SCM+13]
Sven Schlarb, Peter Cliff, Peter May, William Palmer, Matthias Hahn, Reinhold Huber-Moerk, Alexander Schindler, Rainer Schmidt, and Johan van der Knijff. Quality assured image file format migration in large digital object repositories. In Proceedings of the 10th International Conference on Digital Preservation (IPres2013) to appear, Lisbon, Portugal, September 2-5 2013. [ bib| pdf ]
[HMS13b]
Reinhold Huber-Moerk and Alexander Schindler. A keypoint based approach for content characterization in document collections. In Proceedings of the 9th International Symposium on Visual Computing (ISVC'13) to appear, Rethymnon, Crete, Greece, July 29-31 2013. [ bib| pdf ]
[SR12]
Alexander Schindler and Andreas Rauber. Capturing the temporal domain in echonest features for improved classification effectiveness. In Adaptive Multimedia Retrieval, Lecture Notes in Computer Science, Copenhagen, Denmark, October 24-25 2012. Springer. [ bib | .pdf ]
[RSS+12]
Andreas Rauber, Alexander Schindler, Nicu Sebe, Henning Müller, Shara Monteleone, Yiannis Kompatsiaris, Spiros Nikolopoulos, Alexis Joly, and Henri Gouraud. Latest trends in multimedia search computing. In Nicu Sebe, editor, Latest Trends in Multimedia Search Computing (Media Search Cluster White Paper). European Commission - Infomation Society and Media, December 2012. [ bib | .pdf ]
[HMSS12]
Reinhold Huber-Moerk, Alexander Schindler, and Sven Schlarb. Duplicate detection for quality assurance of document image collections. In Proceedings of the 9th International Conference on Digital Preservation (IPres2012), Toronto, Canada, October 1-5 2012. [ bib | .pdf ]
[GHMS12]
Roman Graf, Reinhold Huber-Moerk, and Alexander Schindler. An expert system for quality assurance of document image collections. In Proceedings of the International Conference on Cultural Heritage (EuroMed2012), Lecture Notes in Computer Science, Lemesos, Cyprus, October 29 - November 3 2012. Springer. [ bib | .pdf ]
[SMR12]
Alexander Schindler, Rudolf Mayer, and Andreas Rauber. Facilitating comprehensive benchmarking experiments on the million song dataset. In Proceedings of the 13th International Society for Music Information Retrieval Conference (ISMIR 2012), pages 469-474, Porto, Portugal, October 8-12 2012. [ bib | .pdf ]
[HMS12]
Reinhold Huber-Moerk and Alexander Schindler. Quality assurance for document image collections in digital preservation. In Proceedings of the 14th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2012), Lecture Notes in Computer Science, Brno, Czech Republic, September 4-7 2012. Springer. [ bib | .pdf ]
[Sch11]
Alexander Schindler. Million song dataset integration into the clubmixer framework. In Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), Miami, USA, October 24-28 2011. [ bib | .pdf ]
[GHMS11]
Roman Graf, Reinhold Huber-Moerk, and Alexander Schindler. Quality assurance for scalable braille web service using human interaction by a computer vision system. In Post-conference Proceedings of the International Conference on Integrated Information (IC-ININFO 2011), Kos Island, Greece, September 29 2011. [ bib | .pdf ]
[SR10]
Alexander Schindler and Andreas Rauber. Clubmixer: A presentation platform for mir projects. In Marcin Detyniecki, Peter Knees, Andreas Nürnberger, Markus Schedl, and Sebastian Stober, editors, Adaptive Multimedia Retrieval. Context, Exploration and Fusion Adaptive Multimedia Retrieval. Context, Exploration and Fusion, volume 6817 of Lecture Notes in Computer Science, Linz, Austria, August 17-18 2010. Springer. [ bib | .pdf ]
[Sch10]
Alexander Schindler. Quality of Service Driven Workflows - within the Microsoft .NET Environment. ngs of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), Miami, USA, October 24-28 2011. [ bib | .pdf ]
[GHMh09]
Alexander Schindler. Quality of service driven workflows within the microsoft .net environment. Master's thesis, Vienna University of Technology, 2009. [ bib | .pdf ]