Trepo - Selaus tekijän mukaan "Gabbouj, Moncef"
Viitteet 1-20 / 123
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1D Convolutional Neural Networks and Applications - A Survey
(14.04.2020)
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
(02.02.2021)
article<p>Binary 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 ... -
Acceleration Approaches for Big Data Analysis
(06.09.2018)
conferenceThe 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 (19.01.2021)
conference<p>An 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)
editorialThe 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)
article<p>In 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 ... -
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
(22.12.2018)
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 ... -
BRSR-OpGAN: Blind radar signal restoration using operational generative adversarial network
(10 / 2025)
articleMany studies on radar signal restoration in the literature focus on isolated restoration problems, such as denoising over a certain type of noise, while ignoring other types of artifacts. Additionally, these approaches ... -
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 ... -
Class-wise Generalization Error: an Information-Theoretic analysis
(2025)
articleExisting generalization theories for supervised learning typically take a holistic approach and provide bounds for the expected generalization over the whole data distribution, which implicitly assumes that the model ... -
Classification of polarimetric SAR images using compact convolutional neural networks
(22.12.2020)
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 ... -
Comprehensive Complexity Assessment of Emerging Learned Image Compression on CPU and GPU
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (2023)
conferenceLearned 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 ... -
Convolutional autoencoder-based multimodal one-class classification
(2025)
conferenceOne-class classification refers to approaches of learning using data from a single class only. In this paper, we propose a deep learning one-class classification method suitable for multimodal data, which relies on two ... -
Convolutional Sparse Support Estimator Network (CSEN): From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing
(2021)
article<p>Support 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 ... -
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. ...
