Browsing by Author "Bouridane, Ahmed"
Now showing items 1-12 of 12
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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 ... -
Digital forensic analysis for source video identification: A survey
( Elsevier , 2022 , Article Review)In recent years, many digital devices have been equipped with a video camera that allows videos to be recorded in good quality, free of charge and without restrictions. Concurrently, the widespread use of digital videos ... -
Digitization And Indexing Of Arabic Historical Manuscripts In Qatar
( Hamad bin Khalifa University Press (HBKU Press) , 2014 , Conference)Background Hundreds of thousands of rare Arabic manuscripts are available in Qatar. A rich archival heritage of Islamic world and Qatar are preserved in the Qatar National Library (QNL). A number of international projects ... -
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 ... -
Effectiveness of combined time-frequency imageand signal-based features for improving the detection and classification of epileptic seizure activities in EEG signals
( IEEE , 2014 , Conference)This paper presents new time-frequency (T-F) features to improve the detection and classification of epileptic seizure activities in EEG signals. Most previous methods were based only on signal features derived from the ... -
Enhancing the Prediction of Breast Cancer Progression Through Multi-modal Data Transformation
( Springer , 2025 , Article)The ability to predict breast cancer metastases is essential for making effective clinical decisions and managing patients. Traditional models predominantly rely on structured clinical data, which often lacks essential ... -
Haralick feature extraction from time-frequency images for epileptic seizure detection and classification of EEG data
( IEEE , 2014 , Conference)This paper presents novel time-frequency (t-f) features based on t-f image descriptors for the automatic detection and classification of epileptic seizure activities in EEG data. Most previous methods were based only on ... -
Histopathology in focus: a review on explainable multi-modal approaches for breast cancer diagnosis
( Frontiers Media SA , 2024 , Article Review)Precision and timeliness in breast cancer detection are paramount for improving patient outcomes. Traditional diagnostic methods have predominantly relied on unimodal approaches, but recent advancements in medical data ... -
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 ... -
Simultaneous instance pooling and bag representation selection approach for multiple-instance learning (MIL) using vision transformer
( Springer Science and Business Media Deutschland GmbH , 2024 , Article)In multiple-instance learning (MIL), the existing bag encoding and attention-based pooling approaches assume that the instances in the bag have no relationship among them. This assumption is unsuited, as the instances in ... -
Video steganography: recent advances and challenges
( Springer , 2023 , Article)Video steganography approach enables hiding chunks of secret information inside video sequences. The features of video sequences including high capacity as well as complex structure make them more preferable for choosing ... -
WSNet - Convolutional Neural Networkbased Word Spotting for Arabic and English Handwritten Documents
( UIKTEN - Association for Information Communication Technology Education and Science , 2022 , Article)This paper proposes a new convolutional neural network architecture to tackle the problem of word spotting in handwritten documents. A Deep learning approach using a novel Convolutional Neural Network is developed for the ...
