Publications

This page lists peer-reviewed journal articles, conference proceedings, book chapters, and software outputs related to visual AI, video quality assessment, human visual perception, signal processing, and computer vision.

Peer-reviewed Journal Articles

• Mozhaeva A, Cree MJ, Durrant RJ, Vlasuyk I, Potashnikov A, Mazin V, Streeter L (2024). A contrast sensitivity model of the human visual system in modern conditions for presenting video content. PLoS ONE, 19(5). DOI
• Mozhaeva A (2023, in press). Video quality assessment adapted for TV signals considering modern media content transmission features. Radio Engineering.
• Votyakov SY, Detusheva PV, Mazin VA, Fast SS, Mozhaeva AI (2023). MTUCI Database with Constant Subjective Assessment: Research and Device for Generating Video Sequences of Constant Quality. DSPA: Application Issues of Digital Signal Processing, 13(3), 12–19.
• Mozhaeva A, Vashenko E, Selivanov V, Potashnikov A, Vlasuyk I, Streeter L (2022). Analysis of current video databases for quality assessment. T-Comm, 16(2), 48–56.
• Mozhaeva A, Vlasyuk I, Nezhivleva K, Komina A (2022). Methodology for creating a stimulus for quantitative assessment of the flicker effect in video compression. Systems for Synchronization, Formation and Processing of Signals, 13(6), 29–36.
• Vyatkin M, Potashnikov A, Selivanov V, Vlasuyk I, Nezhivleva K, Mozhaeva A (2022). Method of preventing leakage of personal data through eyetracking modules of user devices. T-Comm, 16(7), 44–51.
• Akhromeiko DS, Zhuravlev AD, Safonov IA, Mozhaeva AI, Streeter L (2022). Analysis of modern encoding standards for streaming video transmission. DSPA: Application Issues of Digital Signal Processing, no. 3.
• Vlasyuk IV, Pashkovskaya AR, Myasnikova VS, Nikolskaya DI, Mozhaeva AI (2022). Analysis of the cost of creation of modern databases of video sequences with subjective quality assessment. DSPA: Application Issues of Digital Signal Processing, no. 1.
• Davydova AA, Mozhaeva AI, Khurani VK, Demina MA, Rusalimov MA (2022). Methodology for studying the identity of perception of user interest regions when viewing streaming video containing various content and compression artifacts. Systems for Synchronization, Formation and Processing of Signals, 13(6), 42–51.
• Potashnikov AM, Mozhaeva AI (2021). Study of the threshold resolution of the human visual system for the primary colours of the RGB system. DSPA: Issues of Application of Digital Signal Processing, 11(1), 3–10.
• Mozhaeva AI, Vlasyuk IV, Potashnikov AM, Streeter L (2021). A reference objective metric for assessing video quality compatible with PSNR considers frequency and peripheral characteristics of human vision. DSPA: Issues of Application of Digital Signal Processing, 11(2), 44–54.

Peer-reviewed Conference Proceedings

• Mozhaeva A, Vlasuyk I, Potashnikov A, Rogers S, Delmas P (2025). Visual Artificial Intelligence: Unlocking Efficiency with Psychovisual Models. International Conference on Image and Vision Computing New Zealand, Wellington, New Zealand, pp. 1–6.
• Mozhaeva A, Vlasuyk I, Alani N, Rogers S, Streeter L (2025). Enhancing Wide-Angle VR Video Transmission Using Human Perception. International Conference on Image and Vision Computing New Zealand, Wellington, New Zealand, pp. 1–6.
• Wijewardana D, Alexander J, Adel A, Fedorov F, Alani N, Mozhaeva A (2025). From Lab to Real-World: Industrially Oriented AI Training Without High-Performance Hardware. International Conference on Engineering Management of Communication and Technology, Vienna, Austria, pp. 1–6.
• Mozhaeva A, Vlasuyk I, Potashnikov A, Mazin V, Streeter L (2024). Video Quality Metric Compatible with PSNR Considering Recent Knowledge of Peripheral Characteristics of Human Vision. 39th International Conference on Image and Vision Computing New Zealand, Christchurch, New Zealand, pp. 1–6. DOI
• Vlasuyk I, Potashnikov A, Mazin V, Mozhaeva A, Egorov D (2024). A Measurement Method and a Mathematical Model of the Human Vision System's Temporal Peripheral Characteristics. Systems of Signals Generating and Processing in the Field of On-Board Communications, pp. 1–7. DOI
• Potashnikov A, Mozhaeva A, Vlasuyk I, Mazin V, Egorov D (2024). Research of the Dependence of the Sensitivity of the Visual System on the Geometric Dimensions of the Stimuli in the Perception of a Typical Multimedia Content. 36th Conference of Open Innovations Association, Lappeenranta, Finland, pp. 617–625. DOI
• Mozhaeva A, Mazin V, Cree MJ, Streeter L (2023). NRspttemVQA: Real-Time Video Quality Assessment Based on the User’s Visual Perception. 38th International Conference on Image and Vision Computing New Zealand, Palmerston North, New Zealand, pp. 1–7. DOI
• Egorova A, Baryshev R, Mozhaeva A (2023). Methodology of researching perception identity of regions of users' interests while viewing streaming video containing various content and compression artefacts. Systems of Signals Generating and Processing in the Field of On-Board Communications, pp. 114–120. DOI
• Mazin V, Cree MJ, Streeter L, Nezhivleva K, Mozhaeva A (2023). Research and application of the adaptive model of the human visual system for improving the effectiveness of objective video quality metrics. 33rd Conference of Open Innovations Association FRUCT, pp. 192–197. DOI
• Drebuzhan AM, Nezhivleva KI, Potashnikov AM, Vlasuyk IV, Mozhaeva AI (2022). The steganographic method of introducing additional information, resistant to transcoding and conversion. Systems of Signals Generating and Processing in the Field of On-Board Communications. DOI
• Egorov DA, Fedorov VD, Vlasuyk IV, Potashnikov AM, Mozhaeva AI (2022). A novel method for estimating the spatial frequency characteristics of cameras based on generative random sequences. Systems of Signals Generating and Processing in the Field of On-Board Communications. DOI
• Nezhivleva KI, Davydova AA, Drebuzhan AM, Mozhaeva AI, Balobanov A (2022). Comparing of modern methods used to assess the quality of video sequences during signal streaming with and without human perception. Systems of Signal Synchronization, Generating and Processing in Telecommunications. DOI
• Potashnikov AM, Mazin VA, Stepanov NS, Smirnov AP, Mozhaeva AI (2022). Analysis of Modern Methods Used to Assess the Quality of Video Sequences During Signal Streaming. Systems of Signals Generating and Processing in the Field of On-Board Communications. DOI
• Mozhaeva A, Potashnikov A, Vlasuyk I, Streeter L (2021). Constant subjective quality database: the research and device of generating video sequences of constant quality. International Conference on Engineering Management of Communication and Technology. DOI
• Potashnikov AM, Mozhaeva AI, Vlasuyk IV, Fedorov VD, Balobanov AV (2021). The method of forming a panorama with increased resolution in the spatial direction. Systems of Signals Generating and Processing in the Field of On-Board Communications. DOI
• Mozhaeva A, Streeter L, Vlasuyk I, Potashnikov A (2021). Full reference video quality assessment metric on base human visual system consistent with PSNR. 28th Conference of Open Innovations Association FRUCT, pp. 309–315. DOI
• Mozhaeva A, Vlasuyk I, Potashnikov A, Cree M, Streeter L (2021). The method and devices for research the parameters of the human visual system to video quality assessment. Systems of Signals Generating and Processing in the Field of On-Board Communications, pp. 1–5. DOI

Peer-reviewed Book Chapters / Books Edited

• Mozhaeva A, Mazin V, Cree MJ, Streeter L (2022). Video quality assessment considering the features of the human visual system. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, pp. 288–300. DOI

Software