| Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat M Al-Sarayreh, MM Reis, WQ Yan, R Klette Food Control 117, 107332, 2020 | 87 | 2020 |
| Detection of red-meat adulteration by deep spectral–spatial features in hyperspectral images M Al-Sarayreh, M M. Reis, W Qi Yan, R Klette Journal of Imaging 4 (5), 63, 2018 | 84 | 2018 |
| Chemometrics and hyperspectral imaging applied to assessment of chemical, textural and structural characteristics of meat MM Reis, R Van Beers, M Al-Sarayreh, P Shorten, WQ Yan, W Saeys, ... Meat science 144, 100-109, 2018 | 65 | 2018 |
| A global calibration model for prediction of intramuscular fat and pH in red meat using hyperspectral imaging Y Dixit, M Al-Sarayreh, CR Craigie, MM Reis Meat Science 181, 108405, 2021 | 36 | 2021 |
| Identification of weeds based on hyperspectral imaging and machine learning Y Li, M Al-Sarayreh, K Irie, D Hackell, G Bourdot, MM Reis, K Ghamkhar Frontiers in Plant Science 11, 611622, 2021 | 35 | 2021 |
| Deep spectral-spatial features of snapshot hyperspectral images for red-meat classification M Al-Sarayreh, MM Reis, WQ Yan, R Klette 2018 international conference on image and vision computing New Zealand …, 2018 | 32 | 2018 |
| A sequential CNN approach for foreign object detection in hyperspectral images M Al-Sarayreh, MM Reis, WQ Yan, R Klette Computer Analysis of Images and Patterns: 18th International Conference …, 2019 | 31 | 2019 |
| Hyperspectral imaging and deep learning for quantification of Clostridium sporogenes spores in food products using 1D-convolutional neural networks and random forest model A Soni, M Al-Sarayreh, MM Reis, G Brightwell Food Research International 147, 110577, 2021 | 26 | 2021 |
| Reducing the pain: A novel tool for efficient ground-truth labelling in images CJ Rapson, BC Seet, MA Naeem, JE Lee, M Al-Sarayreh, R Klette 2018 international conference on image and vision computing New Zealand …, 2018 | 17 | 2018 |
| Detection of adulteration in red meat species using hyperspectral imaging M Al-Sarayreh, MM Reis, WQ Yan, R Klette Image and Video Technology: 8th Pacific-Rim Symposium, PSIVT 2017, Wuhan …, 2018 | 15 | 2018 |
| Identification of cold spots using non-destructive hyperspectral imaging technology in model food processed by coaxially induced microwave pasteurization and sterilization A Soni, M Al-Sarayreh, MM Reis, J Smith, K Tong, G Brightwell Foods 9 (6), 837, 2020 | 7 | 2020 |
| A critical review of social media research in sensory-consumer science SC Hutchings, Y Dixit, M Al-Sarayreh, DD Torrico, CE Realini, SR Jaeger, ... Food Research International 165, 112494, 2023 | 6 | 2023 |
| M., Qi Yan, W., & Klette, R.(2018). Detection of Red-Meat Adulteration by Deep Spectral–Spatial Features in Hyperspectral Images M Al-Sarayreh, M Reis Journal of Imaging 4 (5), 63, 0 | 5 | |
| Hyperspectral imaging and deep learning for food safety assessment M Al-Sarayreh Auckland University of Technology, 2020 | 4 | 2020 |
| Inverse design and ai/deep generative networks in food design: a comprehensive review M Al-Sarayreh, MG Reis, A Carr, MM dos Reis Trends in Food Science & Technology, 2023 | 3 | 2023 |
| A rapid method of hypercube stitching for snapshot multi-camera system Y Dixit, M Al-Sarayreh, C Craigie, MM Reis 2020 35th International Conference on Image and Vision Computing New Zealand …, 2020 | 1 | 2020 |
| Detection and spatial analysis of fairy circles M Al-Sarayreh, Z Moayed, B Bollard-Breen, JB Ramond, R Klette 2016 International Conference on Image and Vision Computing New Zealand …, 2016 | 1 | 2016 |
| ExtSpecR: An R Package and Tool for Extracting Tree Spectra from UAV-Based Remote Sensing Z Liu, M Al-Sarayreh, C Xu, F Tomasetto, Y Li Plant Phenomics 5, 0103, 2023 | | 2023 |
| Corrigendum: Classification of tree symbiotic fungi based on hyperspectral imagery and hybrid convolutional neural networks Z Liu, M Al-Sarayreh, Y Li, Z Yuan Frontiers in Forests and Global Change 6, 1285232, 2023 | | 2023 |
| Classification of tree symbiotic fungi based on hyperspectral imagery and hybrid convolutional neural networks Z Liu, M Al-Sarayreh, Y Li, Z Yuan Frontiers in Forests and Global Change 6, 105, 2023 | | 2023 |
Reinhard KletteAuckland University of TechnologyVerified email at auckland.ac.nz
