Indexed/Peer-reviewed Journals

 

  1. Dikwatta U, Fernando TGI &  Ariyaratne MKA (2024). Exploring mechanisms for detecting violent content in Sinhala image posts: Rationale with unsupervised vs supervised techniques. International Journal of Research in Computing (IJRC)(ISSN 2820-2147 (For the on-line issues)(ISSN 2820-2139 (For the print issues)). General Sir John Kotelawala Defence University, Kandawala Road, Rathmalana, Sri Lanka.

  2. Heenkenda HMSCR & Fernando TGI (2023). Chronological attribution of Sinhalese inscriptions using deep learning approaches. Journal of the National Science Foundation of Sri Lanka. https://doi.org/10.4038/jnsfsr.v51i3.11200.

  3. Ilmini WMKS & Fernando TGI (2023). Detection and explanation of apparent personality using deep learning: a short review of current approaches and future directions. Computing. https://doi.org/10.1007/s00607-023-01221-6.

  4. Ilmini WMKS & Fernando TGI (2023). “Explaining the Outputs of Convolutional Neural Network – Recurrent Neural Network (CNN-RNN) Based Apparent Personality Detection Models Using the Class Activation Maps.” International Journal of  Advanced Computer Science and Applications (IJACSA), vol. 14, no. 2, Feb. 2023, https://thesai.org/Publications/ViewPaper?Volume=14&Issue=2&Code=IJACSA&SerialNo=24.

  5. Ilmini WMKS & Fernando TGI (2022). Performance Analysis of State-of-the-Art Deep Learning Models in the Visual-Based Apparent Personality Detection. Vidyodaya Journal of Science, 25(02). https://doi.org/10.31357/vjs.v25i02.6174

  6. Sirisuriya SCMS, Fernando TGI, & Ariyaratne MKA (2022). Algorithms for path optimizations: a short survey. Springer Computing. https://doi.org/10.1007/s00607-022-01126-w

  7. Heenkenda HMSCR, & Fernando TGI (2020). Approaches Used to Recognize and Decipher Ancient Inscriptions: A Review. Vidyodaya Journal of Science, 23(02). http://journals.sjp.ac.lk/index.php/vjs/article/view/4792

  8. Jayanka M, & Fernando TGI (2020). Recognising Ayurvedic Herbal Plants in Sri Lanka using Convolutional Neural Networks. Vidyodaya Journal of Science, 23(01). https://doi.org/10.31357/vjs.v23i01.4680]

  9. Pemarathne WPJ, & Fernando TGI (2020). Optimising Electrical Wiring Design of a Single-Storey Floor Plan using Multi-Objective Ant Colony System Algorithm (MOACS-EWR). Vidyodaya Journal of Science, 23(01). https://doi.org/10.31357/vjs.v23i01.4677

  10. Ariyaratne MKA, Fernando TGI, & Weerakoon S (2020). A self-tuning algorithm to approximate roots of systems of nonlinear equations based on the firefly algorithm. International Journal of Swarm Intelligence, 2020 Vol.5 No.1, pp.60 – 96. DOI: 10.1504/IJSI.2020.106406

  11. Pemarathne WPJ, & Fernando TGI (2020). Multi objective ant colony algorithm for electrical wire routing. International Journal of Swarm Intelligence, 2020 Vol.5 No.1, pp.97 – 135. DOI: 10.1504/IJSI.2020.106411

  12. Dikwatta U & Fernando TGI (2019). Violence Detection in Social Media – Review. Vidyodaya Journal of Science, 22(2).

  13. Ariyasingha IDID & Fernando TGI (2019). A New Multi-Objective Ant Colony Optimisation Algorithm for Solving the Quadratic Assignment Problem. Vidyodaya Journal of Science, 22(1).

  14. Ariyaratne MKA, Fernando TGI, Weerakoon S (2018). A self-tuning firefly algorithm to tune the parameters of ant colony system. International Journal of Swarm Intelligence, Inderscience Publishers. 2018 Vol.3, No.4, pp.309 – 331.

  15. Nishani HPS, Weerakoon S, Fernando TGI, & Liyanage M. (2018). Weerakoon-Fernando Method with accelerated third-order convergence for systems of nonlinear equations. International Journal of Mathematical Modelling and Numerical Optimisation [Internet]. 2018 [cited 2018 Jan 7];8(3):287.

  16. Ariyasingha IDID & Fernando TGI (2017). Random weight-based ant colony optimization algorithm for the multi-objective optimization problems. International Journal of Swarm Intelligence, Inderscience Publishers. 2017 Jan 1;3(1):77-100.

  17. Ariyaratne MKA & Fernando TGI, Weerakoon S. (2016). An archived firefly algorithm; a mathematical software to solve univariate nonlinear equations. International Journal on Advances in ICT for Emerging Regions (ICTer). 2016 Jul 13;9(1).

  18. Ilmini WMKS & Fernando TGI (2016). Persons Personality Traits Recognition using Machine Learning Algorithms and Image Processing Techniques. Advances in Computer Science: an International Journal. 2016 Jan 31;5(1):40-4.

  19. Ariyasingha IDID & Fernando TGI (2015). A Performance Study for the Multi-objective Ant Colony Optimization Algorithms on the Job Shop Scheduling Problem. International Journal of Computer Applications. 2015 17-12;132(14):1-8.

  20. Ariyaratne MKA & Fernando TGI (2014). A Comparative Study on Nature Inspired Algorithms with Firefly Algorithm. The International Journal of Engineering and Technology (IJET)(ISSN 2049-3444), Vol. 04, No 10, Oct. 2014.

  21. Wanigasooriya J & Fernando TGI (2013). Multi-Vehicle Passenger Allocation and Route Optimization for Employee Transportation using Genetic Algorithms. International Journal of Computer Applications. 2013 15-2;64(20):1-9.

  22. Fernando TGI & Kalganova T (2012). Multi-Colony Ant Systems for Multi-Hose Routing. International Journal of Computer Applications. 2012 18-12; 59(2):114.

  23. Abeysooriya RP, Fernando TGI (2012). Hybrid Approach to Optimize Cut Order Plan Solutions in Apparel Manufacturing. International Journal of Information and Communication Technology Research, Vol. 2, No. 4, Apr. 2012.

  24. Abeysooriya RP & Fernando TGI (2012). Canonical Genetic Algorithm To Optimize Cut Order Plan Solutions in Apparel Manufacturing. Journal of Emerging Trends in Computing and Information Sciences. Vol. 3, No. 2, Feb. 2012.

  25. Udeshani KAG, Meegama RGN, & Fernando TGI (2011). Statistical Feature-based Neural Network Approach for the Detection of Lung Cancer in Chest X-Ray Images. International Journal of Image Processing, vol. 5, Issue. 4, 2011.

  26. Thantulage G & Kalganova T, Wilson M (2006). Grid-Based and Random Based Ant Colony Algorithms for Automatic Hose Routing in 3D Space. Transactions on Engineering, Computing and Technology, Volume 14, International Journal of Applied Science, Engineering and Technology (IJASET), Enformatika, ISBN 1503-5313, ISBN 975-00803-3-5, Aug. 2006. pp. 144 – 150, 2006.