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Combining Saliency with Prediction for Endoscopic Diagnosis
(2020-05)
Healthcare sector has advanced tremendously in the past few years. With the advancement in technology, many image diagnostic techniques have been introduced to help doctors in identifying diseases and abnormalities inside ...
Face Flow: Constrained Optical Flow Framework for Faces
(2020-05)
In computer vision, models and methods for facial expression recognition are continually in development. Several models aim to describe the highly complex structure of different faces, which in turn allows researchers to ...
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 ...
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 ...
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 ...
Distinguishing Between Fake and Real Smiles Using EEG Signals and Deep Learning
(2020-04)
Genuineness of smiles is one aspect of the field of deception recognition, one that is prevalent in myriad social situations, and it is not easy to tell when a person’s smile is genuine or not for the average person. Machine ...
Arabic Multimodal Emotion Recognition Using Deep Learning
(2022-05)
Emotions are an essential part of human communication since it shapes how information is received. As part of human-computer interaction, researchers are extending Emotion Recognition (ER) to machines. ER can contribute ...