首页|New Intelligent Systems Findings Has Been Reported by Investigators at Sidi Moha med Ben Abdellah University (Octonion-based Transform Moments for Innovative Ste reo Image Classification With Deep Learning)
New Intelligent Systems Findings Has Been Reported by Investigators at Sidi Moha med Ben Abdellah University (Octonion-based Transform Moments for Innovative Ste reo Image Classification With Deep Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Machine Learning-Intelligent Systems. According to news reporting out of Fes, Morocco, by NewsRx editors, research stated, "Recent advances in imaging technologies h ave led to a significant increase in the adoption of stereoscopic images. Howeve r, despite this proliferation, in-depth research into the complex analysis of th e visual content of these stereoscopic images is still relatively rare." Financial support for this research came from King Saud University. Our news journalists obtained a quote from the research from Sidi Mohamed Ben Ab dellah University, "The advent of stereoscopic imaging has brought a new dimensi on to visual content. These images offer a higher level of visual detail, making them increasingly common in a variety of fields, including medicine and industr ial applications. However, exploiting the full potential of stereoscopic images requires a deeper understanding. By exploiting the capabilities of octonion mome nts and the power of artificial intelligence, we aim to break new ground by intr oducing a novel method for classifying stereoscopic images. The proposed method is divided into two key stages: The first stage involves data preprocessing, dur ing which we strive to construct a balanced database divided into three distinct categories. In addition, we extract the stable Octonion Krawtchouk moments (SOK M) for each image, leading to a database of moment images with dimensions of 128 x 128 x 1. In the second step, we train a convolutional neural network (CNN) mo del using this database, with the aim of discriminating between different catego ries. Standard measures such as precision, accuracy, recall, F1 score, and ROC c urves are used to assess the effectiveness of our method."
FesMoroccoAfricaIntelligent System sMachine LearningSidi Mohamed Ben Abdellah University
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