Computer Analysis of Art by Jane Tarakhovsky
Computer Analysis of Art, ACM Journal on Computing and Cultural Heritage, vol. 5, no. 2, article 7. ACM, 2012.
Astronomical Anomalies
LSST Galaxy Structural Analysis
Computational analysis using ~125,000 spiral galaxies showed asymmetry between clockwise and counterclockwise spinning galaxies. Such observation is in conflict with some of the basic assumptions on which modern cosmology is based. The study was published in the journal Physics Letters B. An article about the study was published in the magazine New Scientist.
Computational Astronomy by Evan Kuminski
Large Synoptic Survey Telescope (LSST)
Combining human and machine learning for morphological analysis of galaxy images, Publications of the Astronomical Society of the Pacific, In Press.
Whale FM by Carol Yerby: Learning the whale language
Understanding the communication of whales is important not just for expanding our knowledge, but also for protecting this endangered species. LTU/MCS is now taking part in a large international project that aims at profiling the way whales communicate. The project includes several years of audio data acquired by using special audio sensors attached to the whales, and while watching the whales in their natural environment from ships. LTU’s part in the project is to develop pattern recognition and machine learning algorithms, and apply these algorithms to mine hours of data recordings and tens of thousands of whale communication recording samples. Our machine learning methods are trained with the help of over 800,000 volunteers who annotate the data manually. Our first findings have been accepted for publication in the prestigious Journal of the Acoustical Society of America
In the project LTU is part of a collaboration that includes researchers from Woods Hole Oceanographic Institute, St. Andrews University, Oxford University (UK) and TNO (Netherlands). The project also involves LTU student Carol Yerby, who is one of the authors of the paper.
Classification of large acoustic datasets using machine learning and crowdsourcing - application to whale calls, Journal of the Acoustical Society of America, vol. 135(2), pp. 953-962. AIP. 2014.
Improving bird conservation using computational bird perception
by Sarah Svatora
Effective nesting box | Ineffective nesting box |
Sarah Svatora presented her senior project, in which she developed a computational method based on bird psychology and vision in combination with spatial parameters that can improve nesting box efficacy by up to 50%. Her pioneering research will allow better protection and preservation of blue birds, and can be extended to other species. Sarah was the keynote speaker at the event.
Improving Eastern Bluebird nest box performance using computer analysis of satellite images. Computational Ecology and Software, vol.2, no. 2, p. 96-102. IAEES, 2012.
Elderly Fall Prevention Research
Most serious and intractable problem in elder care
70 million elders will fall annually by 2020
15% visit an emergency room
40% are hospitalized and enter residential care
Many will never return to independent living again
Sparrow Research Project
Observes the elderly while alone
Anticipates an unassisted egress
Notifies caregivers anywhere
Elderly Fall Notification Research
Undergraduate Student led research projects
Demonstrated at Henry Ford Hospital
Based on Microsoft Kinect Game Technology
Chris: Student presenter |
Intelligent Ground Vehicle Competition (IGVC) Team 2015 - BigFoot
(Left to right: Prof. CJ Chung, Icaro Gargione, Prof. Jonathan Ruszala, Gordon Stein, Jimmy Tanamati Soares, and Fan Wei)
The IGVC challenges student teams to develop an autonomous & interoperable ground vehicle that can maneuver in lanes and through chicanes and flags while also finding six GPS waypoints along the way. Research topics in this project includes artificial intelligence, computer vision, sensor-fusion, UDP based network software, real-time embedded software engineering, CPS (Cyber Physical Systems), and IoRT (Internet of Robotic Things). All the technologies of this project can be directly applied to the development of self-driving and connected vehicles.
Complex Software Development while having fun at the same time!