Browsing Department of Computer Science and Engineering by Subject "Deep learning"
Now showing items 1-4 of 4
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AgroAId: A Mobile App System for Visual Classification of Plant Species and Diseases Using Deep Learning and TensorFlow Lite
(MDPI, 2022)This paper aims to assist novice gardeners in identifying plant diseases to circumvent misdiagnosing their plants and to increase general horticultural knowledge for better plant growth. In this paper, we develop a mobile ... -
Classifying Maqams of Qur'anic Recitations Using Deep Learning
(IEEE Access, 2021)The Holy Qur’an is among the most recited and memorized books in the world. For beautification of Qur’anic recitation, almost all reciters around the globe perform their recitations using a specific melody, known as maqam ... -
In-Between Projection Interpolation in Cone-Beam CT Imaging using Convolutional Neural Networks
(Society of Photo-Optical Instrumentation Engineers (SPIE), 2022)Respiratory-Correlated cone beam computed tomography (4D-CBCT) is an emerging image-guided radiation therapy (IGRT) technique that is used to account for the uncertainties caused by respiratory-induced motion in the ... -
Two-Stage Deep Learning Solution for Continuous Arabic Sign Language Recognition Using Word Count Prediction and Motion Images
(IEEE, 2023)Recognition of continuous sign language is challenging as the number of words is a sentence and their boundaries are unknown during the recognition stage. This work proposes a two-stage solution in which the number of words ...