I am currently focusing on Deep Learning AI applications to Australian industries.

Teaching

• CP2406: Programming III (Level 2; TSV)
• CP3101: Professional Internship (Level 3; TSV)
• CP3103: Independent Project (Level 3; TSV)
• CP3405: Design Thinking and Project Management (Level 3; TSV)
• CP3406: Mobile Computing (Level 3; CNS & TSV)
• CP5046: ICT Project 1: Analysis and Design (Level 5; CNS & TSV)
• CP5047: ICT Project 2: Implementation and Commissioning (Level 5; CNS & TSV)
• CP5307: Advanced Mobile Technology (Level 5; TSV)

Interests

Research

• Computer vision with Convolutional Neural Networks
• Application of Deep Learning AI to Northern Australia Beef Industry, Aquaculture, Australian Great Barrier Reef monitoring

Experience

• 2002 to present - Senior Lecturer, James Cook University (Townsville)

Research Disciplines

• Computer vision and multimedia computation (4603)
• Machine learning (4611)

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles

• Dexter B, King R, Parisi A, Harrison S, Konovalov D and Downs N (2020) Keratinocyte skin cancer risks for working school teachers: scenarios and implications of the timing of scheduled duty periods in Queensland, Australia. Journal of Photochemistry and Photobiology B: Biology, 213, Article: 112046, DOI:10.1016/j.jphotobiol.2020.112046.
• Konovalov D, Swinhoe N, Efremova D, Birtles R, Kusetic M, Hillcoat S, Curnock M, Williams G and Sheaves M (2020) Automatic sorting of Dwarf Minke Whale underwater images. Information, 11 (4), Article: 200, DOI:10.3390/info11040200.
• Saleh A, Laradji I, Konovalov D, Bradley M, Vazquez D and Sheaves M (2020) A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis. Scientific Reports, 10, Article: 14671, DOI:10.1038/s41598-020-71639-x.
• Sheaves M, Bradley M, Herrera C, Mattone C, Lennard C, Sheaves J and Konovalov D (in press) Optimizing video sampling for juvenile fish surveys: using deep learning and evaluation of assumptions to produce critical fisheries parameters. Fish and Fisheries, , DOI:10.1111/faf.12501.
• Olsen A, Konovalov D, Philippa B, Ridd P, Wood J, Johns J, Banks W, Girgenti B, Kenny O, Whinney J, Calvert B, Rahimi Azghadi M and White R (2019) DeepWeeds: a multiclass weed species image dataset for deep learning. Scientific Reports, 9, Article: 2058, DOI:10.1038/s41598-018-38343-3.
• Glassen T, Oertzen T and Konovalov D (2018) Finding the mean in a partition distribution. BMC Bioinformatics, 19, Article: 375, DOI:10.1186/s12859-018-2359-z.

Conference Papers

• Konovalov D, Swinhoe N, Efremova D, Birtles R, Kusetic M, Adams K, Hillcoat S, Curnock M, Williams G, Sobtzick S and Sheaves M (2020) Minke whale detection in underwater imagery using classification CNNs. Proceedings of Global Oceans 2020. In: Global Oceans 2020: Singapore – U.S. Gulf Coast, 5-30 October 2020, Biloxi, MS, USA
• Efremova D, Sankupellay M and Konovalov D (2019) Data-efficient classification of birdcall through Convolutional Neural Networks transfer learning. Proceedings of the International Conference on Digital Image Computing. In: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia
• Konovalov D, Saleh A, Efremova D, Domingos J and Jerry D (2019) Automatic weight estimation of harvested fish from images. Proceedings of the International Conference on Digital Image Computing. In: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia
• Konovalov D, Saleh A, Bradley M, Sankupellay M, Marini S and Sheaves M (2019) Underwater fish detection with weak multi-domain supervision. Proceedings of the International Joint Conference on Neural Networks. In: 2019 IJCNN: International Joint Conference on Neural Networks, 14-19 July 2019, Budapest, Hungary
• Lapico A, Sankupellay M, Cianciullo L, Myers T, Konovalov D, Jerry D, Toole P, Jones D and Zenger K (2019) Using image processing to automatically measure pearl oyster size for selective breeding. Proceedings of the International Conference on Digital Image Computing. In: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia
• Wang J, Sankupellay M, Konovalov D, Towsey M and Roe P (2019) Social network analysis of an acoustic environment: the use of visualised data to characterise natural habitats. Proceedings of the International Conference on Digital Image Computing. In: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia

More

ResearchOnline@JCU stores 39+ research outputs authored by Dr Dmitry Konovalov from 2004 onwards.

Current and recent Research Funding to JCU is shown by funding source and project.

Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

Current

• Edge Artificial Intelligence for Marine Monitoring (PhD , Primary Advisor)
• Smart Sensors, Low Cost Radio Network System and the Internet of Things to Improve Effluent Quality from Algal Waste Treatment Systems and Aquaculture (Masters , Secondary Advisor)

Completed

• Developing Deep Learning Methods For Aquaculture Applications (2020, Masters , Primary Advisor)

The map shows research collaborations by institution from the past 7 years.
Note: Map points are indicative of the countries or states that institutions are associated with.