Saudi Cultural Missions Theses & Dissertations
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Item Restricted Rasm: Arabic Handwritten Character Recognition: A Data Quality Approach(University of Essex, 2024) Alghamdi, Tawfeeq; Doctor, FaiyazThe problem of AHCR is a challenging one due to the complexities of the Arabic script, and the variability in handwriting (especially for children). In this context, we present ‘Rasm’, a data quality approach that can significantly improve the result of AHCR problem, through a combination of preprocessing, augmentation, and filtering techniques. We use the Hijja dataset, which consists of samples from children from age 7 to age 12, and by applying advanced preprocessing steps and label-specific targeted augmentation, we achieve a significant improvement of a CNN performance from 85% to 96%. The key contribution of this work is to shed light on the importance of data quality for handwriting recognition. Despite the recent advances in deep learning, our result reveals the critical role of data quality in this task. The data-centric approach proposed in this work can be useful for other recognition tasks, and other languages in the future. We believe that this work has an important implication on improving AHCR systems for an educational context, where the variability in handwriting is high. Future work can extend the proposed techniques to other scripts and recognition tasks, to further improve the optical character recognition field.50 0Item Restricted IN-LABORATORY SIMPLIFIED IMAGE-BASED EMPIRICAL POLARIMETRIC BIDIRECTIONAL REFLECTANCE DISTRIBUTION FUNCTION MEASUREMENT USING 3D GEOMETRIC TARGETS(University of Dayton, 2024-04-21) Aldkeelalah, Sultan; Ratliff, BradleyThe bidirectional reflectance distribution function (BRDF) is essential to remote sensing, computer graphics, and material science applications. It aids the development of photo-realistic rendering models, target detection and recognition, and atmospheric characterization tasks in remote sensing. BRDF measurements are cumbersome to make, requiring dense, full hemispherical sampling that often results in millions of individual measurements conducted at precise sensor and illumination source geometries. Methods have been proposed based upon theoretical, experimental, and empirical approaches that aim to simplify the data collection process. Empirically, researchers have proposed using targets of different geometric shapes in conjunction with image-based sensors to acquire measurements in parallel, thus reducing the acquisition time. This work surveys studies of such proposed methods to measure BRDF/polarimetric BRDF (pBRDF). Our group previously presented a fast and simple framework for empirically measuring the pBRDF using a linear imaging polarimeter from novel 3D-printed geodesic target spheres with well-characterized surface facets under outdoor environmental conditions. The models derived from this approach were validated against physics-based models and demonstrated good agreement. In this work, we present a modified approach to conduct similar measurements on the same faceted objects in a laboratory environment. The Applied Sensing Lab at the University of Dayton has constructed a solar simulation laboratory that allows for highly accurate and repeatable positioning of light sources, sensors, and objects. The laboratory contains both collimated (direct sun) and diffuse (downwelling) light sources that we have spectrally tuned in this work to match expected solar irradiance under a range of outdoor conditions. The laboratory-based pBRDF models obtained by our proposed framework validate strongly against their corresponding outdoor, spectroradiometric measurements (ground truth), and physics-based models.27 0