"Gabbouj, Moncef" - Selaus tekijän mukaan TUNICRIS-julkaisut
Viitteet 1-20 / 116
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1D Convolutional Neural Networks and Applications - A Survey
(04 / 2021)
articleDuring the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Artificial Neural Networks (ANNs) with ... -
3D Quantum Cuts for automatic segmentation of porous media in tomography images
(02 / 2022)
articleBinary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves ... -
Acceleration Approaches for Big Data Analysis
(IEEE, 06.09.2018)
conferenceObjectThe massive size of data that needs to be processed by Machine Learning models nowadays sets new challenges related to their computational complexity and memory footprint. These challenges span all processing steps involved ... -
Advance Warning Methodologies for COVID-19 Using Chest X-Ray Images
(2021)
articleCoronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning system for the early diagnosis of COVID-19 ... -
AnomalyHop : An SSL-based Image Anomaly Localization Method
Visual communications and image processing (IEEE, 19.01.2021)
conferenceObjectAn image anomaly localization method based on the successive subspace learning (SSL) framework, called Anomaly-Hop, is proposed in this work. AnomalyHop consists of three modules: 1) feature extraction via successive ... -
Applied Artificial Intelligence and Machine Learning for Video Coding and Streaming : Editorial
(2021)
articleThe papers in this special section focus on applied artificial inteligence and machine learning for video coding and media streaming. -
Attention-based Neural Bag-of-Features Learning for Sequence Data
(2022)
articleIn this paper, we propose 2D-Attention (2DA), a generic attention formulation for sequence data, which acts as a complementary computation block that can detect and focus on relevant sources of information for the given ... -
Automatic image-based identification and biomass estimation of invertebrates
(2020)
articleUnderstanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming ... -
Bag of Color Features For Color Constancy
(2020)
articleIn this paper, we propose a novel color constancy approach, called Bag of Color Features (BoCF), building upon the Bag-of-Feature pooling, which allows for reducing the number of parameters needed for illumination estimation ... -
Benchmark dataset for mid‐price forecasting of limit order book data with machine learning methods
(12 / 2018)
articleManaging the prediction of metrics in high‐frequency financial markets is a challenging task. An efficient way is by monitoring the dynamics of a limit order book to identify the information edge. This paper describes the ... -
Blind ECG Restoration by Operational Cycle-GANs
(2022)
articleObjective: ECG recordings often suffer from a set of artifacts with varying types, severities, and durations, and this makes an accurate diagnosis by machines or medical doctors difficult and unreliable. Numerous studies ... -
Channel-wise Feature Decorrelation for Enhanced Learned Image Compression
(2024)
articleThe emerging Learned Compression (LC) replaces the traditional codec modules with Deep Neural Networks (DNN), which are trained end-to-end for rate-distortion performance. This approach is considered as the future of ... -
Classification of polarimetric SAR images using compact convolutional neural networks
(2021)
articleClassification of polarimetric synthetic aperture radar (PolSAR) images is an active research area with a major role in environmental applications. The traditional Machine Learning (ML) methods proposed in this domain ... -
Coding of mixed-resolution multiview video in 3D video application
IEEE International Conference on Image Processing (Institute of Electrical and Electronics Engineers IEEE, 2013)
conferenceObjectThe emerging MVC+D standard specifies the coding of Multiview Video plus Depth (MVD) data for enabling advanced 3D video applications. MVC+D specifications define the coding of all views of MVD at equal spatial resolution ... -
Complexity Analysis of Next-Generation HEVC Decoder
IEEE International Symposium on Circuits and Systems (Institute of Electrical and Electronics Engineers IEEE, 2012)
conferenceObjectThis paper analyzes the complexity of the HEVC video decoder being developed by the JCT-VC community. The HEVC reference decoder HM 3.1 is profiled with Intel VTune on Intel Core 2 Duo processor. The analysis covers both ... -
Comprehensive Complexity Assessment of Emerging Learned Image Compression on CPU and GPU
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2023)
conferenceObjectLearned Compression (LC) is the emerging technology for compressing image and video content, using deep neural networks. Despite being new, LC methods have already gained a compression efficiency comparable to state-of-the-art ... -
Content-based Audio Classification using Collective Network of Binary Classifiers
IEEE Conference on Evolving and Adaptive Intelligence Systems (IEEE, 2011)
conferenceObjectIn this paper, a novel collective network of binary classifiers (CNBC) framework is presented for content-based audio classification. The topic has been studied in several publications before, but in many cases the number ... -
Convolutional Sparse Support Estimator Network (CSEN) : From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing
(2023)
articleSupport estimation (SE) of a sparse signal refers to finding the location indices of the nonzero elements in a sparse representation. Most of the traditional approaches dealing with SE problems are iterative algorithms ... -
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
(05 / 2021)
articleCoronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ...
