Browsing NTNU Open by Author "Yazidi, Anis"
Now showing items 1-20 of 60
-
A General Formalism for Defining and Detecting OpenFlow Rule Anomalies
Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E.; Kure, Øivind (Chapter, 2017)SDN network's policies are updated dynamically at a high pace. As a result, conflicts between policies are prone to occur. Due to the large number of switches and heterogeneous policies within a typical SDN network, detecting ... -
A Multi-View Self-Supervised Approach to Learn Representations of EEG Data for Downstream Prediction Tasks
Hojjati, Amirabbas (Master thesis, 2023)Denne avhandlingen presenterer en selvovervåket dyp læringstilnærming for å lære og trekke ut representasjoner fra langtids-electroencephalogram (EEG) inndata, for å bli brukt i nedstrømsoppgaver som prediksjon av demens, ... -
An Analysis of Data Production Based on the Consistency of Decision Matrices
Sahin, Bekir; Yazidi, Anis; Roman, Dumitru; Uddin, Md Zia; Soylu, Ahmet (Peer reviewed; Journal article, 2021)Multi-criteria decision making methods are used to solve numerous problems related to several disciplines such as engineering, management and business. Consistency of a decision making application is of crucial importance ... -
Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review
Khan, Haroon; Naseer, Noman; Yazidi, Anis; Eide, Per Kristian; Hassan, Wajahat; Mirtaheri, Peyman (Peer reviewed; Journal article, 2021)Human gait is a complex activity that requires high coordination between the central nervous system, the limb, and the musculoskeletal system. More research is needed to understand the latter coordination's complexity in ... -
Artificial intelligence in the fertility clinic: status, pitfalls and possibilities
Riegler, Michael Alexander; Stensen, Mette Haug; Witczak, Oliwia; Andersen, Jorunn Marie; Hicks, Steven; Hammer, Hugo Lewi; Delbarre, Erwan; Halvorsen, Pål; Yazidi, Anis; Holst, Nicolai; Haugen, Trine B. (Journal article; Peer reviewed, 2021)In recent years, the amount of data produced in the field of ART has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, artificial intelligence (AI) is progressively ... -
Automated well log depth matching: Late fusion multimodal deep learning
Torres Caceres, Veronica Alejandra; Duffaut, Kenneth; Yazidi, Anis; Westad, Frank Ove; Johansen, Yngve Bolstad (Peer reviewed; Journal article, 2022)Petrophysical interpretation and optimal correlation extraction of different measurements require accurate well log depth matching. We have developed a supervised multimodal machine learning alternative for the task of ... -
Automated Well-Log Depth Matching – 1D Convolutional Neural Networks Vs. Classic Cross Correlation
Torres Caceres, Veronica Alejandra; Duffaut, Kenneth; Yazidi, Anis; Westad, Frank Ove; Johansen, Yngve Bolstad (Peer reviewed; Journal article, 2022)During drilling and logging, depth alignment of well logs acquired in the same borehole section at different times is a vital preprocessing step before any petrophysical analysis. Depth alignment requires high precision ... -
AWkS: adaptive, weighted k‑means‑based superpixels for improved saliency detection
Gupta, Ashish Kumar; Seal, Ayan; Yazidi, Anis (Peer reviewed; Journal article, 2020)Clustering inspired superpixel algorithms perform a restricted partitioning of an image, where each visually coherent region containing perceptually similar pixels serves as a primitive in subsequent processing stages. ... -
Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow
Yazidi, Anis; Abolpour Mofrad, Asieh; Goodwin, Morten; Hammer, Hugo Lewi; Arntzen, Erik (Peer reviewed; Journal article, 2020)An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner ... -
Benchmarks for machine learning in depression discrimination using electroencephalography signals
Seal, Ayan; Bajpai, Rishabh; Karnati, Mohan; Agnihotri, Jagriti; Yazidi, Anis; Herrera-Viedma, Enrique; Krejcar, Ondrej (Journal article; Peer reviewed, 2022)Diagnosis of depression using electroencephalography (EEG) is an emerging field of study. When mental health facilities are unavailable, the use of EEG as an objective measure for depression management at an individual ... -
Classification of Individual Finger Movements from Right Hand Using fNIRS Signal
Khan, Haroon; Noori, Farzan Majeed; Yazidi, Anis; Uddin, Md Zia; Khan, M.N Afzal; Mirtaheri, Peyman (Peer reviewed; Journal article, 2021)Functional near-infrared spectroscopy (fNIRS) is a comparatively new noninvasive, portable, and easy-to-use brain imaging modality. However, complicated dexterous tasks such as individual finger-tapping, particularly using ... -
Clustering Uncertain Data Objects Using Jeffreys-Divergence and Maximum Bipartite Matching Based Similarity Measure
Sharma, Krishna Kumar; Seal, Ayan; Yazidi, Anis; Selamat, Ali; Krejcar, Ondrej (Peer reviewed; Journal article, 2021)In recent years, uncertain data clustering has become the subject of active research in many fields, for example, pattern recognition, and machine learning. Nowadays, researchers have committed themselves to substitute the ... -
Comparative Analysis of Functional Connectivity Metrics in EEG Datasets
Maratova, Assem; Lencastre, Pedro; Yazidi, Anis; Lind, Pedro (Journal article, 2023)Analysis of functional connectivity helps to determine how brain regions interact with one another and to understand neurological diseases better. In this study, we compare functional connectivity networks derived from ... -
Contrastive autoencoder for anomaly detection in multivariate time series
Zhou, Hao; Yu, Ke; Zhang, Xuan; Wu, Guanlin; Yazidi, Anis (Peer reviewed; Journal article, 2022)With the proliferation of the Internet of Things, a large amount of multivariate time series (MTS) data is being produced daily by industrial systems, corresponding in many cases to life-critical tasks. The recent anomaly ... -
A deep CNN model for anomaly detection and localization in wireless capsule endoscopy images
Jain, Samir; Seal, Ayan; Ojha, Aparajita; Yazidi, Anis; Bures, Jan; Tacheci, Ilja; Krejcar, Ondrej (Peer reviewed; Journal article, 2021)Wireless capsule endoscopy (WCE) is one of the most efficient methods for the examination of gastrointestinal tracts. Computer-aided intelligent diagnostic tools alleviate the challenges faced during manual inspection of ... -
A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering
Thunold, Håvard Horgen; Riegler, Michael; Yazidi, Anis; Hammer, Hugo Lewi (Journal article; Peer reviewed, 2023)An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient data ... -
A Dual-Channel Dehaze-Net for Single Image Dehazing in Visual Internet of Things Using PYNQ-Z2 Board
Sahu, Geet; Seal, Ayan; Yazidi, Anis; Krejcar, Ondrej (Peer reviewed; Journal article, 2024) -
A dynamic and scalable parallel Network Intrusion Detection System using intelligent rule ordering and Network Function Virtualization
Haugerud, Hårek; Tran, Huy Nhut; Aitsaadi, Nadjib; Yazidi, Anis (Journal article; Peer reviewed, 2021)A Network Intrusion Detection System (NIDS) is a fundamental security tool. However, under heavy network traffic, a NIDS might become a bottleneck. In an overloaded state, incoming and outgoing packets in the network might ... -
Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes
Abolpour Mofrad, Asieh; Yazidi, Anis; Abolpour Mofrad, Samaneh; Hammer, Hugo Lewi; Arntzen, Erik (Peer reviewed; Journal article, 2021)Formation of stimulus equivalence classes has been recently modeled through equivalence projective simulation (EPS), a modified version of a projective simulation (PS) learning agent. PS is endowed with an episodic memory ... -
Enhancing security attacks analysis using regularized machine learning techniques
Hagos, Desta Haileselassie; Yazidi, Anis; Kure, Øivind; Engelstad, Paal E. (Journal article; Peer reviewed, 2017)With the increasing threats of security attacks, Machine learning (ML) has become a popular technique to detect those attacks. However, most of the ML approaches are black-box methods and their inner-workings are difficult ...