Aisha Ajmal

 

 

aisha.ajmal@yoobeecolleges.com

 

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About

Aisha Ajmal is a faculty member of the School of Technology in Software Engineering at Yoobee Colleges of Creative Innovation. She is a computer engineer, specialising in Artificial Intelligence and Computer Vision. Her research focuses on image processing and object detection techniques.

Aisha is currently working towards her Doctor of Philosophy candidacy in Artificial Intelligence at Victoria University of Wellington. Her completed master’s thesis is based on the human vision system (HVS), which collects a vast amount of data and performs a variety of biological mechanisms to select relevant information. Computational models based on these biological mechanisms are used in machine vision to select interesting or salient regions in images for application in scene analysis, object detection and object tracking. Aisha hypothesized that the integration of a visual attention model with object tracking can be effective in increasing performance by reducing detection complexity in challenging environments such as illumination change, occlusion, and camera movement. She developed a visual saliency-based object tracker that alternates between targets using a measure of current uncertainty derived from a Kalman filter. She also compared non-uniform red, green and blue (RGB) derived opponencies with hue, saturation and value (HSV) colour space using video information. The results were used to improve the quality of saliency detection in challenging situations such as lighting change.

Academic Qualification

MSc: Master of Science (Computer Science)

Victoria University of Wellington, Wellington, New Zealand, 2020

Thesis: Active shift attention based object tracking system

MSc: Master of Science (Computer Engineering)

Sir Syed University of Engineering and Technology (SSUET), Karachi, Pakistan, 2014

BSc: Bachelor of Science (Computer Engineering)

Sir Syed University of Engineering and Technology (SSUET), Karachi, Pakistan, 2009

Research Outputs

Publications

Theses and Dissertations (Open Access)

Ajmal, A. (2020). Active shift attention based object tracking system [Masters thesis, Victoria University of Wellington]. https://researcharchive.vuw.ac.nz/xmlui/handle/10063/9233

eBooks

Ajmal, A., Harith-Al-Sahaf, & Hollitt, C. (2020). Salient motion features for visual attention models. In Proceedings of the 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), Wellington, New Zealand, pp. 1-6. https://ieeexplore.ieee.org/abstract/document/9290712

Ajmal, A., Hollitt, C., Frean, M., & Harith Al-Sahaf (2018). A comparison of RGB and HSV colour spaces for visual attention models. In Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ), Auckland, New Zealand, pp. 1-6. https://ieeexplore.ieee.org/abstract/document/8634752

Ajmal, A., Hollitt, C., Frean, M. (2017). Active shift attention based object tracking system. In Proceedings of the International Conference on Image and Vision Computing New Zealand (IVCNZ), Christchurch, New Zealand, pp. 1-5. https://ieeexplore.ieee.org/abstract/document/8402491

Ajmal, A., Hussain, I. M. (2012). A simple and novel method for vehicle detection and classification (a model based test). In Proceedings of 2012 9th International Bhurban Conference on Applied Sciences & Technology (IBCAST), pp. 58-63. https://ieeexplore.ieee.org/document/6177527

Khan, M. K., Naseem, M., Hussain, I. M., & Ajmal, A. (2011). Distributed least significant bit technique for data hiding in images. In Proceedings of IEEE 14th International Multitopic Conference, pp. 149-154. https://ieeexplore.ieee.org/abstract/document/6151461

Ajmal, A., Hussain, I. M. (2010). Vehicle detection using morphological image processing technique. In Proceedings of International Conference on Multimedia Computing and Information Technology (MCIT), 65-68. https://ieeexplore.ieee.org/abstract/document/5444851

Journal Articles

Hussain, I. M., Ajmal, A. (2013). SMS security based on 2-way handshaking method using data hiding algorithm. International Journal of Electronics, Computer and Communications Technologies 3(4), 26-33. https://journal.uniten.edu.my/index.php/ijecct/article/view/70

Hussain, I. M., Khan, M. K., Naseem, M., Ajmal, A., Hussain, O. M. (2012). Improved bit plane splicing LSB technique for secret data hiding in images using linear congruent method. I.J. Image, Graphics and Signal Processing (7), 1-14. https://www.mecs-press.org/ijigsp/ijigsp-v4-n7/IJIGSP-V4-N7-1.pdf

Naseem, M., Hussain, I. M., Khan, M. K., & Ajmal, A. (2011). An optimum modified bit plane splicing LSB algorithm for secret data hiding. International Journal of Computer Applications 29(12), 36-43. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=0fb67bcf9a5b20877274cf16a559db14f77b3e2e

Rehan Rasheed, M., Khan, M. K., Naseem, M., Ajmal, A., & Hussain, I. M. (2010). Performance of routing protocols in WiMAX networks. International Journal of Engineering and Technology 2(5), 412. http://www.ijetch.org/papers/157-T269.pdf

Ajmal, A., & Hussain, I. M. (2009). Morphological process based vehicle detection and classification. MASAUM Journal of Basic and Applied Sciences 1(2), 213-220. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=870608ddaa9b7e9987e4e072a1abba95bdfbea96