| Computer vision and machine learning analysis of commercial rice grains: A potential digital approach for consumer perception studies A Aznan, C Gonzalez Viejo, A Pang, S Fuentes Sensors 21 (19), 6354, 2021 | 32 | 2021 |
| Rapid detection of fraudulent rice using low-cost digital sensing devices and machine learning A Aznan, C Gonzalez Viejo, A Pang, S Fuentes Sensors 22 (22), 8655, 2022 | 21 | 2022 |
| The use of machine vision technique to classify cultivated rice seed variety and weedy rice seed variants for the seed industry. AA Aznan, IH Rukunudin, AYM Shakaff, R Ruslan, A Zakaria, FSA Saad International Food Research Journal 23, 2016 | 19 | 2016 |
| Rice seed varieties identification based on extracted colour features using image processing and artificial neural network (ANN) AA Aznan, R Ruslan, IH Rukunudin, FA Azizan, AY Hashim Int. J. Adv. Sci. Eng. Inf. Technol 7 (6), 2220-2225, 2017 | 16 | 2017 |
| Soil NPK variability mapping for Harumanis mango grown in greenhouse at Perlis, Malaysia FA Azizan, N Roslan, R Ruslan, AA Aznan, AZM Yusoff International Journal on Advanced Science, Engineering and Information …, 2019 | 15 | 2019 |
| Review of technology advances to assess rice quality traits and consumer perception A Aznan, CG Viejo, A Pang, S Fuentes Food Research International 172, 113105, 2023 | 11 | 2023 |
| Extraction of morphological features of malaysian rice seed varieties using flatbed scanner R Ruslan, AA Aznan, FA Azizan, N Roslan, N Zulkifli Int. J. Adv. Sci. Eng. Inf. Technol 8 (1), 93-98, 2018 | 11 | 2018 |
| Rapid assessment of rice quality traits using low-cost digital technologies A Aznan, C Gonzalez Viejo, A Pang, S Fuentes Foods 11 (9), 1181, 2022 | 8 | 2022 |
| Growth monitoring of Harumanis mango leaves (Mangifera Indica) at vegetative stage using SPAD meter and leaf area meter N Roslan, AA Aznan, R Ruslan, MN Jaafar, FA Azizan IOP Conference Series: Materials Science and Engineering 557 (1), 012010, 2019 | 7 | 2019 |
| Groundwater assessment using geophysical survey at Insat, Perlis, Malaysia FA Azizan, AA Aznan, R Ruslan, M Nazari, MN Jaafar IOP Conference Series: Materials Science and Engineering 429 (1), 012026, 2018 | 7 | 2018 |
| Effect of Background Color on Rice Seed Image Segmentation using Machine Vision R Ruslan, MF Ibrahim, S Khairunniza-Bejo, AA Aznan, IH Rukunudin, ... 2018 International Conference on Computational Approach in Smart Systems …, 2018 | 7 | 2018 |
| Analysis of spatial distribution of soil moisture content for different soil layers in mango greenhouse FA Azizan, FNM Zalani, A Nagarajan, AA Aznan, R Ruslan IOP Conference Series: Materials Science and Engineering 557 (1), 012070, 2019 | 4 | 2019 |
| Specific energy consumption and drying efficiency analysis of commercial mixed-flow batch type seed drying system MZ Azmi, IH Rukunudin, HA Ismail, AA Aznan Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 55 (1 …, 2019 | 3 | 2019 |
| Application of image processing technique to extract morphological characteristics of weedy rice seeds variants for Malaysian seed industry AA Aznan, IH Rukunudin, AYM Shakaff, R Ruslan, A Zakaria, FSA Saad Advances in Environmental Biology, 112-116, 2014 | 3 | 2014 |
| Assessment of carbohydrate contents in perlis harumanis mango leaves during vegetative and productive growth NH Hazis, AA Aznan, MN Jaafar, FA Azizan, R Ruslan, IH Rukunudin IOP Conference Series: Materials Science and Engineering 429 (1), 012025, 2018 | 2 | 2018 |
| Rapid detection of rice adulteration using a low-cost electronic nose and machine learning modelling A Aznan, C Gonzalez Viejo, A Pang, S Fuentes Engineering Proceedings 27 (1), 1, 2022 | 1 | 2022 |
| Spatial and temporal variability in the harumanis mango leaves at vegetative stage in a greenhouse N Roslan, R Ruslan, MN Jaafar, AA Aznan, FA Azizan, IH Rukunudin | 1 | 2006 |
| Selection of Morphological Features in Classifying Weedy Rice and Rice Seed Varieties using Discriminant Function Analysis R Ruslan, SK Bejo, IH Rukunuddin, AA Aznan IOP Conference Series: Materials Science and Engineering 557 (1), 012014, 2019 | | 2019 |
| The use of machine vision technique to classify cultivated rice seed variety and weedy rice seed variants for the seed industry AYM Shakaff, IH Rukunudin, R Ruslan, A Zakaria, AA Aznan, FSA Saad International Food Research Journal (Malaysia), 2016 | | 2016 |
| Identification of Cultivated Rice MR 263 Seed and Weedy Rice Seed Variants Using CCD Camera Based-machine Vision System AA Aznan School of Bioprocess Engineering, Universiti Malaysia Perlis, 2015 | | 2015 |
