Browsing by Author "Akbari, Younes"
Now showing items 1-11 of 11
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Attention-based Network for Image/Video Salient Object Detection
(2023 , Article)The goal of video or image salient object detection is to identify the most important object in the scene, which can be helpful in many computer vision-based tasks. As the human vision framework has a successful capacity ... -
Automated systems for diagnosis of dysgraphia in children: a survey and novel framework
( Springer Science and Business Media Deutschland GmbH , 2024 , Article)Learning disabilities, which primarily interfere with basic learning skills such as reading, writing, and math, are known to affect around 10% of children in the world. The poor motor skills and motor coordination as part ... -
Backbones-review: Feature extractor networks for deep learning and deep reinforcement learning approaches in computer vision
( Elsevier Ireland Ltd , 2024 , Article)To understand the real world using various types of data, Artificial Intelligence (AI) is the most used technique nowadays. While finding the pattern within the analyzed data represents the main task. This is performed by ... -
Bi-attention DoubleUNet: A deep learning approach for carotid artery segmentation in transverse view images for non-invasive stenosis diagnosis
( Elsevier , 2024 , Article)The carotid artery is a vital blood vessel that supplies oxygenated blood to the brain. Blockages in this artery can lead to life-threatening illnesses, making accurate diagnosis essential. While ultrasound (US) imaging ... -
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
( Elsevier , 2023 , Article)Dysgraphia is a neurological disorder that hinders the acquisition process of normal writing skills in children, resulting in poor writing abilities. Poor or underdeveloped writing skills in children can negatively impact ... -
Edge Detection with multi-scale representation and refined Network
( Institution of Engineering and Technology , 2022 , Conference)Edge detection is a representation of boundaries between objects and regions in an image. Due to the variations of types, scales, intensities as well as background, the detection of these boundaries represents a challenge ... -
Exploration and analysis of On-Surface and In-Air handwriting attributes to improve dysgraphia disorder diagnosis in children based on machine learning methods
( Elsevier , 2023 , Article)Dysgraphia is a type of learning disorder that affects children’s writing skills. Poor writing skills can obstruct students’ academic growth if it is undiagnosed and untreated properly in the early stages. The irregularity ... -
Exploring Classification Models for Video Source Device Identification: A Study of CNN-SVM and Softmax Classifier
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Conference)Video Source device identification plays a crucial role in video forensics as the proliferation of video capturing devices has given rise to crimes with videos that are challenging to trace. Reliance on metadata extraction ... -
A New Dataset for Forged Smartphone Videos Detection: Description and Analysis
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Article)The advancement of Internet technology has significantly impacted daily life, which is influenced by digital videos taken with smartphones as the most popular type of multimedia. These digital videos are extensively sent ... -
A New Framework for Smart Doors Using mmWave Radar and Camera-Based Face Detection and Recognition Techniques
( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)By integrating IoT technology, smart door locks can provide greater convenience, security, and remote access. This paper presents a novel framework for smart doors that combines face detection and recognition techniques ... -
PRNU Estimation based on Weighted Averaging for Source Smartphone Video Identification
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference)Photo response non-uniformity (PRNU) noise is a sensor pattern noise characterizing imperfections in the imaging device. The PRNU is a unique noise for each sensor device, and it has been generally utilized in the literature ...
