2023 - Research.com Computer Science in Ireland Leader Award
2022 - Research.com Computer Science in Ireland Leader Award
2017 - IEEE Fellow For contributions to multimedia information indexing and retrieval
2015 - Gold Medal, Royal Irish Academy Engineering Sciences
2013 - Member of the Royal Irish Academy
His main research concerns Information retrieval, Artificial intelligence, Multimedia, TRECVID and Digital video. His Artificial intelligence research includes themes of Pattern recognition, Computer vision and Natural language processing. His study in Computer vision is interdisciplinary in nature, drawing from both Lifelog and Wearable computer.
His biological study spans a wide range of topics, including Digital television, Systems design and Hypertext, World Wide Web. His studies deal with areas such as NIST, Video retrieval and Baseline as well as TRECVID. His studies in Video retrieval integrate themes in fields like Feature extraction and Benchmark.
Alan F. Smeaton spends much of his time researching Information retrieval, Multimedia, Artificial intelligence, World Wide Web and TRECVID. Alan F. Smeaton regularly links together related areas like Image retrieval in his Information retrieval studies. In his works, Alan F. Smeaton undertakes multidisciplinary study on Multimedia and Digital video.
His work deals with themes such as Machine learning, Pattern recognition, Computer vision and Natural language processing, which intersect with Artificial intelligence. His TRECVID research is multidisciplinary, relying on both NIST, Feature extraction and Benchmark. Alan F. Smeaton has researched Image processing in several fields, including Lifelog and Wearable computer.
Alan F. Smeaton focuses on Artificial intelligence, Machine learning, TRECVID, Multimedia and Information retrieval. His Artificial intelligence research incorporates themes from Rapid serial visual presentation, Computer vision and Natural language processing. His Computer vision research incorporates elements of Artificial neural network, Visualization and Wearable computer.
His study in TRECVID is interdisciplinary in nature, drawing from both NIST and Closed captioning. His Multimedia study incorporates themes from Class, Computer programming, Analytics and Learning analytics. His study in Video retrieval and Search engine indexing falls under the purview of Information retrieval.
Alan F. Smeaton mainly investigates Artificial intelligence, Learning analytics, TRECVID, Multimedia and Rapid serial visual presentation. His Artificial intelligence research incorporates themes from Machine learning, Computer vision and Natural language processing. His research in Computer vision focuses on subjects like Wearable computer, which are connected to Lifelog and Applied psychology.
The study incorporates disciplines such as Hyperlink, Information retrieval and Closed captioning in addition to TRECVID. His work on Search engine indexing as part of general Information retrieval research is frequently linked to Action, thereby connecting diverse disciplines of science. His Multimedia research includes themes of Obesity and Environmental health.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Evaluation campaigns and TRECVid
Alan F. Smeaton;Paul Over;Wessel Kraaij.
multimedia information retrieval (2006)
TRECVID 2011 - An overview of the goals, tasks, data, evaluation mechanisms, and metrics
P. Over;G. Awad;J. Fiscus;B. Antonishek.
TREC Video Retrieval Evaluation, TRECVID 2011, 5-7 December 2011, Gaithersburg, MD, USA (2012)
TRECVID 2014 - An Overview of the Goals, Tasks, Data, Evaluation Mechanisms, and Metrics
Paul Over;Jon Fiscus;Gregory A. Sanders;David Joy.
Proceedings of TRECvid 2014 (2014)
TRECVID 2012 - An overview of the goals, tasks, data, evaluation mechanisms, and metrics
P. Over;J. Fiscus;G. Sanders;B. Shaw.
TREC Video Retrieval Evaluation, TRECVID 2012, 26-28 November 2012, Gaithersburg, MD. USA (2013)
TRECVID 2013 -- An Overview of the Goals, Tasks, Data, Evaluation Mechanisms and Metrics
P. Over;J. Fiscus;G. Sanders;M. Michel.
TRECVID 2013 : proceedings (2014)
TRECVID 2013 -- An Overview of the Goals, Tasks, Data, Evaluation Mechanisms, and Metrics | NIST
Paul D. Over;Jonathan G. Fiscus;Gregory A. Sanders;David M. Joy.
TRECVID Publications Home (2014)
On Using Twitter to Monitor Political Sentiment and Predict Election Results
Adam Bermingham;Alan Smeaton.
Proceedings of the Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2011) (2011)
Classifying sentiment in microblogs: is brevity an advantage?
Adam Bermingham;Alan F. Smeaton.
conference on information and knowledge management (2010)
Lifelogging: Personal Big Data
Cathal Gurrin;Alan F. Smeaton;Aiden R. Doherty.
Video shot boundary detection: Seven years of TRECVid activity
Alan F. Smeaton;Paul Over;Aiden R. Doherty.
Computer Vision and Image Understanding (2010)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: