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

2022: 2nd place finish in NASA-sponsored Mars Spectrometry 2: Gas Chromatography Challenge: https://drivendata.co/blog/mars-2-gcms-challenge-winners

Teaching

• BU3102: Multidisciplinary Project (Level 3; TSV)
• CP2406: Programming III (Level 2; TSV)
• CP2410: Algorithms and Data Structures (Level 2; TSV)
• CP3102: Multidisciplinary Project (Level 3; TSV)
• CP3403: Data Mining (Level 3; CNS & TSV)
• CP3406: Mobile Computing (Level 3; TSV)
• CP3407: Advanced Software Engineering (Level 3; TSV)
• CP5047: ICT Project 2: Implementation and Commissioning (Level 5; CNS & TSV)
• CP5307: Advanced Mobile Technology (Level 5; TSV)
• CP5634: Data Mining (Level 5; CNS & TSV)

Interests

Professional

• 2022: Kaggle Competitions Expert https://www.kaggle.com/dmitrykonovalov

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)
• Veterinary sciences (3009)
• Machine learning (4611)

Socio-Economic Objectives

• Expanding knowledge (2801)
• Marine systems and management (1805)

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

• Joone C and Konovalov D (2023) The effect of neuter status on longevity in the Rottweiler dog. Scientific Reports, 13 (1).
• Kophamel S, Ward L, Konovalov D, Mendez D, Ariel E, Cassidy N, Bell I, Balastegui Martínez M and Munns S (2022) Field?based adipose tissue quantification in sea turtles using bioelectrical impedance spectroscopy validated with CT scans and deep learning. Ecology and Evolution, 12.
• Mattone C, Bradley M, Barnett A, Konovalov D and Sheaves M (2022) Environmental conditions constrain nursery habitat value in Australian sub-tropical estuaries. Marine Environmental Research, 175.
• Josi D, Heg D, Takeyama T, Bonfils D, Konovalov D, Frommen J, Kohda M and Taborsky M (2021) Age‐ and sex‐dependent variation in relatedness corresponds to reproductive skew, territory inheritance and workload in cooperatively breeding cichlids. Evolution, 75 (11). pp. 2881-2897
• 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.
• 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).
• 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.
• Sheaves M, Bradley M, Herrera C, Mattone C, Lennard C, Sheaves J and Konovalov D (2020) Optimizing video sampling for juvenile fish surveys: using deep learning and evaluation of assumptions to produce critical fisheries parameters. Fish and Fisheries, 21 (6). pp. 1259-1276

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

More

ResearchOnline@JCU stores 45+ 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.

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.