Browsing by Subject "Support vector machines"
Now showing items 1-20 of 29
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Adaptive Novelty Detection over Contextual Data Streams at the Edge using One-class Classification
(2021)Online novelty detection is an emerging task in Edge Computing trying to identify novel concepts in contextual data streams which should be incorporated into predictive analytics and inferential models locally executed on ... -
Advanced cancer cell characterization and quantification of microscopy images
(2012)In this paper we present an advanced image analysis tool for the accurate characterization and quantification of cancer and apoptotic cells in microscopy images. Adaptive thresholding and Support Vector Machines classifiers ... -
Applying unsupervised and supervised machine learning methodologies in social media textual traffic data
(2019)Traffic increasingly shapes the trajectory of city growth and impacts on the climate change in modern cities. Traffic patterns’ monitoring can provide with innovative practices in understanding city traffic dynamics, ... -
Classification of Driving Behaviour using Short-term and Long-term Summaries of Sensor Data
(2020)The classification of driving behaviour is important for monitoring driving risk and fuel efficiency, as well as for adaptive driving assistance and car insurance industry. Starting from raw measurements of acceleration ... -
Classification of pathological human brain lesions using magnetic resonance spectroscopy at 3T
(2009)Magnetic Resonance Spectroscopy is a powerful non-invasive diagnostic tool that is used in conjunction with MRI techniques to provide identification and quantification of biologically important compounds in soft tissue. ... -
Crowd Sourcing as an Improvement of N-Grams Text Document Classification Algorithm
(2020)A common task in a world of natural language processing is text classification useful for e.g.spam filters, documents sorting, science articles classification or plagiarism detection. This can still be done best and most ... -
Deep Bidirectional and Unidirectional LSTM Neural Networks in Traffic Flow Forecasting from Environmental Factors
(2021)The application of deep learning techniques in several forecasting problems has been increased the last years, in many scientific fields. In this research, a deep learning structure is proposed, composed mainly of double ... -
Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters
(2019)Accurate prediction of water quality parameters plays a crucial and decisive role in environmental monitoring, ecological systems sustainability, human health, aquaculture and improved agricultural practices. In this study ... -
DiS-TSS: An Annotation Agnostic Algorithm for TSS Identification
(2020)The spread, distribution and utilization of transcription start sites (TSS) experimental evidence within promoters are poorly understood. Cap Analysis of Gene Expression (CAGE) has emerged as a popular gene expression ... -
Early Fusion of Visual Representations of Skeletal Data for Human Activity Recognition
(2022)In this work we present an approach for human activity recognition which is based on skeletal motion, i.e., the motion of skeletal joints in the 3D space. More specifically, we propose the use of 4 well-known image ... -
Enhanced human body fall detection utilizing advanced classification of video and motion perceptual components
(2009)The monitoring of human physiological data, in both normal and abnormal situations of activity, is interesting for the purpose of emergency event detection, especially in the case of elderly people living on their own. ... -
Estimation of models for cumulative infiltration of soil using machine learning methods
(2021)Knowledge of cumulative infiltration of soil is necessary for irrigation, surface flow, groundwater recharge and many other hydrological processes. In the present study, the Support Vector Machine (SVM), artificial neural ... -
Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images Based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization
(2021)Wireless capsule endoscopy (WCE) constitutes a medical imaging technology developed for the endoscopic exploration of the gastrointestinal (GI) tract, whereas it provides a more comfortable examination method, in comparison ... -
Feature Selection in Single-Cell RNA-seq Data via a Genetic Algorithm
(2021)Big data methods prevail in the biomedical domain leading to effective and scalable data-driven approaches. Biomedical data are known for their ultra-high dimensionality, especially the ones coming from molecular biology ... -
Forest classification trees and forest support vector machines algorithms: Demonstration using microarray data
(2010)Classification into multiple classes when the measured variables are outnumbered is a major methodological challenge in -omics studies. Two algorithms that overcome the dimensionality problem are presented: the forest ... -
Fusing Handcrafted and Contextual Features for Human Activity Recognition
(2019)In this paper we present an approach for the recognition of human activity that combines handcrafted features from 3D skeletal data and contextual features learnt by a trained deep Convolutional Neural Network (CNN). Our ... -
A fuzzy decision tree-based SVM classifier for assessing osteoarthritis severity using ground reaction force measurements
(2010)A novel fuzzy decision tree-based SVM (FDT-SVM) classifier is proposed in this paper, to distinguish between asymptotic (AS) and osteoarthritis (OA) knee gait patterns and to investigate OA severity using 3-D ground reaction ... -
Improving Multiclass Classification of Cybersecurity Breaches in Railway Infrastructure using Imbalanced Learning
(2021)Machine learning approaches and algorithms are spreading in wide areas in research and technology. Cybersecurity breaches are the common anomalies for networked and distributed infrastructures which are monitored, registered, ... -
Intrusion detection system for platooning connected autonomous vehicles
(2019)The deployment of Connected Autonomous Vehicles (CAVs) in Vehicular Ad Hoc Networks (VANETs) requires secure wireless communication in order to ensure reliable connectivity and safety. However, this wireless communication ... -
Long Short-Term Memory (LSTM) Deep Neural Networks in Energy Appliances Prediction
(2019)The application of Long Short-Term Memory (LSTM) Deep Neural Networks has been increased the last years. This paper proposes a novel methodology based on a hybrid model using the Long Short-Term Memory (LSTM) Networks and ...