Publishing Music Similarity Features on the Semantic Web. - Dan Tidhar; György Fazekas; Sefki Kolozali; Mark B. Sandler (ISMIR, 2009)

Towards the Automatic Generation of a Semantic Web Ontology for Musical Instruments. - Sefki Kolozali; Mathieu Barthet; György Fazekas; Mark B. Sandler (SAMT, 2010)

Knowledge Representation Issues in Musical Instrument Ontology Design. - Sefki Kolozali; Mathieu Barthet; György Fazekas; Mark B. Sandler (ISMIR, 2011)

Automatic Ontology Generation for Musical Instruments Based on Audio Analysis. - Sefki Kolozali; Mathieu Barthet; György Fazekas; Mark B. Sandler (IEEE Trans. Speech Audio Process., 2013)

A Knowledge-Based Approach for Real-Time IoT Data Stream Annotation and Processing. - Sefki Kolozali; María Bermúdez-Edo; Daniel Puschmann; Frieder Ganz; Payam M. Barnaghi (iThings/GreenCom/CPSCom, 2014)

A Framework for Automatic Ontology Generation Based on Semantic Audio Analysis. - Sefki Kolozali; György Fazekas; Mathieu Barthet; Mark B. Sandler (Semantic Audio, 2014)

A Validation Tool for the W3C SSN Ontology based Sensory Semantic Knowledge. - Sefki Kolozali; Tarek Elsaleh; Payam M. Barnaghi (TC/SSN@ISWC, 2014)

Physical-cyber-social similarity analysis in smart cities. - Nazli FarajiDavar; Sefki Kolozali; Payam M. Barnaghi (WF-IoT, 2016)

CityPulse: Large Scale Data Analytics Framework for Smart Cities. - Dan Puiu; Payam M. Barnaghi; Ralf Toenjes; Daniel Kuemper; Muhammad Intizar Ali; Alessandra Mileo; Josiane Xavier Parreira; Marten Fischer; Sefki Kolozali; Nazli FarajiDavar; Feng Gao 003; Thorben Iggena; et al. (IEEE Access, 2016)

On the Effect of Adaptive and Nonadaptive Analysis of Time-Series Sensory Data. - Sefki Kolozali; Daniel Puschmann; María Bermúdez-Edo; Payam M. Barnaghi (IEEE Internet Things J., 2016)

Data analysis as a web service: A case study using IoT sensor data. - Alireza Ahrabian; Sefki Kolozali; Shirin Enshaeifar; Clive Cheong Took; Payam M. Barnaghi (ICASSP, 2017)

A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams. - Nazli FarajiDavar; Sefki Kolozali; Payam M. Barnaghi (CoRR, 2017)

Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams. - Sefki Kolozali; María Bermúdez-Edo; Nazli FarajiDavar; Payam M. Barnaghi; Feng Gao 003; Muhammad Intizar Ali; Alessandra Mileo; Marten Fischer; Thorben Iggena; Daniel Kuemper; Ralf Tönjes (IEEE Internet Things J., 2019)

Best practices for publishing, retrieving, and using spatial data on the web. - Linda van den Brink; Payam M. Barnaghi; Jeremy Tandy; Ghislain Atemezing; Rob Atkinson; Byron Cochrane; Yasmin Fathy; Raúl García-Castro; Armin Haller; Andreas Harth; Krzysztof Janowicz; Sefki Kolozali; et al. (Semantic Web, 2019)

Audio-Based Deep Learning Frameworks for Detecting COVID-19. - Dat Ngo; Lam Pham; Truong Van Hoang; Sefki Kolozali; Delaram Jarchi (EUSIPCO, 2022)

Using Machine Learning for Anomaly Detection on a System-on-Chip under Gamma Radiation. - Eduardo Weber Wächter; Server Kasap; Sefki Kolozali; Xiaojun Zhai; Shoaib Ehsan; Klaus D. McDonald-Maier (CoRR, 2022)

COPD Patient's Symptoms with Personal Environmental Sensors. - Sefki Kolozali (IEEE DataPort, 2022)

An Inception-Residual-Based Architecture with Multi-Objective Loss for Detecting Respiratory Anomalies. - Dat Ngo; Lam Pham; Huy Phan; Minh Tran; Delaram Jarchi; Sefki Kolozali (MMSP, 2023)

Early detection of COPD patients' symptoms with personal environmental sensors: a remote sensing framework using probabilistic latent component analysis with linear dynamic systems. - Sefki Kolozali; Lia Chatzidiakou; Roderic Jones; Jennifer Kathleen Quint; Frank Kelly; Benjamin Barratt (Neural Comput. Appl., 2023)

Explainable Early Prediction of Gestational Diabetes Biomarkers by Combining Medical Background and Wearable Devices: A Pilot Study With a Cohort Group in South Africa. - Sefki Kolozali; Sara L. White; Shane Norris; Maria Fasli; Alastair van Heerden (IEEE J. Biomed. Health Informatics, 2024)