Browsing Qatar University Institutional Repository by Author "Gabbouj M."
Now showing items 21-40 of 52
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Generalized Operational Classifiers for Material Identification
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Material is one of the intrinsic features of objects, and consequently material recognition plays an important role in image understanding. The same material may have various shapes and appearance, while keeping the same ... -
Heterogeneous Multilayer Generalized Operational Perceptron
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)The traditional multilayer perceptron (MLP) using a McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinear thresholding step. Previously, generalized ... -
Human experts vs. machines in taxa recognition
( Elsevier B.V. , 2020 , Article)The step of expert taxa recognition currently slows down the response time of many bioassessments. Shifting to quicker and cheaper state-of-the-art machine learning approaches is still met with expert scepticism towards ... -
K-Subspaces Quantization for Approximate Nearest Neighbor Search
( IEEE Computer Society , 2016 , Article)Approximate Nearest Neighbor (ANN) search has become a popular approach for performing fast and efficient retrieval on very large-scale datasets in recent years, as the size and dimension of data grow continuously. In this ... -
Knowledge Transfer for Face Verification Using Heterogeneous Generalized Operational Perceptrons
( IEEE Computer Society , 2019 , Conference Paper)Face verification is a prominent biometric technique for identity authentication that has been used extensively in several security applications. In practice, face verification is often performed along with other visual ... -
Learned vs. hand-designed features for ECG beat classification: A comprehensive study
( Springer Verlag , 2017 , Conference Paper)In this study, in order to find out the best ECG classification performance we realized comparative evaluations among the state-of-the-art classifiers such as Convolutional Neural Networks (CNNs), multi-layer perceptrons ... -
Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Echocardiogram (echo) is the earliest and the primary tool for identifying regional wall motion abnormalities (RWMA) in order to diagnose myocardial infarction (MI) or commonly known as heart attack. This paper proposes a ... -
Long-term epileptic EEG classification via 2D mapping and textural features
( Elsevier Ltd , 2015 , Article)Interpretation of long-term Electroencephalography (EEG) records is a tiresome task for clinicians. This paper presents an efficient, low cost and novel approach for patient-specific classification of long-term epileptic ... -
Maximum achievable throughput and interference mitigation for SUN in coexistence with WLAN
( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)An optimum packet length selection scheme to maximize the throughput of a smart utility network (SUN) is introduced under wireless local area network (WLAN) interference system. The traditional and the investigated segmented ... -
Multifrequency Polsar Image Classification Using Dual-Band 1D Convolutional Neural Networks
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)In this work, we propose a novel classification approach based on dual-band one-dimensional Convolutional Neural Networks (1D-CNNs) for classification of multifrequency polarimetric SAR (PolSAR) data. The proposed approach ... -
One-Dimensional Convolutional Neural Networks for Real-Time Damage Detection of Rotating Machinery
( Springer , 2022 , Conference Paper)This paper presents a novel real-time rotating machinery damage monitoring system. The system detects, quantifies, and localizes damage in ball bearings in a fast and accurate way using one-dimensional convolutional neural ... -
Operational neural networks
( Springer , 2020 , Article)Feed-forward, fully connected artificial neural networks or the so-called multi-layer perceptrons are well-known universal approximators. However, their learning performance varies significantly depending on the function ... -
Optimization on ports activation towards energy efficient data center networks
( Springer Verlag , 2018 , Conference Paper)Nowadays, Internet of thing including network support (i.e. checking social media, sending emails, video conferencing) requires smart and efficient data centers to support these services. Hence, data centers become more ... -
Particle swarm clustering fitness evaluation with computational centroids
( Elsevier B.V. , 2017 , Article)In this paper, we propose a new way to carry out fitness evaluation in dynamic Particle Swarm Clustering (PSC) with centroid-based encoding. Generally, the PSC fitness function is selected among the clustering validity ... -
Patient-Specific Seizure Detection Using Nonlinear Dynamics and Nullclines
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Nonlinear dynamics has recently been extensively used to study epilepsy due to the complex nature of the neuronal systems. This study presents a novel method that characterizes the dynamic behavior of pediatric seizure ... -
Performance Comparison of Learned vs. Engineered Features for Polarimetric SAR Terrain Classification
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Conference Paper)In this work, we propose to use learned features for terrain classification of Polarimetric Synthetic Aperture Radar (PolSAR) images. In the proposed classification framework, the learned features are extracted from sliding ... -
Progressive Operational Perceptrons
( Elsevier B.V. , 2017 , Article)There are well-known limitations and drawbacks on the performance and robustness of the feed-forward, fully-connected Artificial Neural Networks (ANNs), or the so-called Multi-Layer Perceptrons (MLPs). In this study we ... -
Progressive Operational Perceptrons with Memory
( Elsevier B.V. , 2020 , Article)Generalized Operational Perceptron (GOP) was proposed to generalize the linear neuron model used in the traditional Multilayer Perceptron (MLP) by mimicking the synaptic connections of biological neurons showing nonlinear ... -
PyGOP: A Python library for Generalized Operational Perceptron algorithms
( Elsevier B.V. , 2019 , Article)PyGOP provides a reference implementation of existing algorithms using Generalized Operational Perceptron (GOP), a recently proposed artificial neuron model. The implementation adopts a user-friendly interface while allowing ... -
Real-Time Fault Detection and Identification for MMC Using 1-D Convolutional Neural Networks
( Institute of Electrical and Electronics Engineers Inc. , 2019 , Article)Automated early detection and identification of switch faults are essential in high-voltage applications. Modular multilevel converter (MMC) is a new and promising topology for such applications. MMC is composed of many ...