Parcourir par sujet "Learning systems"
Voici les éléments 21-40 de 96
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DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data
(2022)Background: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE ... -
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification
(2018)This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only ... -
Diagnostic and learning interaction system for historical text comprehension
(2003)In this contribution we present a Learner Model (LM) of Historical Text Comprehension (HTC), which activates the learner in interactive diagnostic and learning dialogues. The LM infers the learner's cognitive profile and ... -
Dialogue-based personalized reflective learning
(2004)The Web-Based Reflective Tutorial Dialogue System (W-ReTuDiS) is a system for personalized learning of historical text comprehension on the Web. The system offers a two level open interface: tutor level and learner level. ... -
EDUC8 pathways: executing self-evolving and personalized intra-organizational educational processes
(2020)One of the main challenges to be confronted by modern tertiary sector, so as to improve quality is the personalization of learning, which has to be combined with a minimization of the respective costs. However, personalization ... -
Emotion recognition from speech: A classroom experiment
(2018)In this position paper we present an approach for the recognition of emotions from speech. Our goal is to understand the affective state of learners upon a learning process. We propose an approach that uses visual ... -
EndoVAE: Generating Endoscopic Images with a Variational Autoencoder
(2022)The generalization performance of deep learning models is closely associated with the number and diversity of data available upon training. While in many applications there is a large number of data available in public, ... -
An Ensemble Interpretable Machine Learning Scheme for Securing Data Quality at the Edge
(2020)Data quality is a significant research subject for any application that requests for analytics to support decision making. It becomes very important when we focus on Internet of Things (IoT) where numerous devices can ... -
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 ... -
ETH analysis and predictions utilizing deep learning
(2020)This paper attempts to provide a data analysis of cryptocurrency markets. Such markets have been developed rapidly and their volatility poses significant research challenges and justifies intensive behavior analysis. For ... -
Evaluating the Effects of Modern Storage Devices on the Efficiency of Parallel Machine Learning Algorithms
(2020)Big Data analytics is presently one of the most emerging areas of research for both organizations and enterprises. The requirement for deployment of efficient machine learning algorithms over huge amounts of data led to ... -
An explainable semi-personalized federated learning model
(2022)Training a model using batch learning requires uniform data storage in a repository. This approach is intrusive, as users have to expose their privacy and exchange sensitive data by sending them to central entities to be ... -
An Exploratory Teaching Proposal of Greek History Independence Events based on STEAM Epistemology, Educational Robotics and Smart Learning Technologies
(2021)Digital technologies help students to delve into the process of scientific discovery. Curriculum integration of STEM contents based on constructivism theories of learning as a context to implement the Science, Technology, ... -
Exploring an ensemble of methods that combines fuzzy cognitive maps and neural networks in solving the time series prediction problem of gas consumption in Greece
(2019)This paper introduced a new ensemble learning approach, based on evolutionary fuzzy cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM-ANN), for time series prediction. The main aim ... -
Exploring deep learning capabilities in knee osteoarthritis case study for classification
(2019)This research study is devoted to the investigation of deep neural networks (DNN) for classification of the complex problem of knee osteoarthritis diagnosis. Osteoarthritis (OA) is the most common chronic condition of the ... -
From undirected structures to directed graphical lasso fuzzy cognitive maps using ranking-based approaches
(2020)Fuzzy cognitive maps (FCMs) have gained popularity within the scientific community due to their capabilities in modelling and decision making for complex problems. However, learning FCM models automatically from data without ... -
FSO links with spatial diversity over strong atmospheric turbulence channels
(2008)Free-space optical (FSO) communication has received much attention in recent years as a cost-effective, license-free and wide-bandwidth access technique for high data rates applications. The performance of FSO communication, ... -
Fuzzy control system for smart energy management in residential buildings based on environmental data
(2021)Modern energy automation solutions and demand response applications rely on load profiles to monitor and manage electricity consumption effectively. The introduction of smart control systems capable of handling additional ... -
Fuzzy Pooling
(2021)Convolutional neural networks (CNNs) are artificial learning systems typically based on two operations: convolution, which implements feature extraction through filtering, and pooling, which implements dimensionality ... -
A game theoretic framework for data privacy preservation in recommender systems
(2011)We address the fundamental tradeoff between privacy preservation and high-quality recommendation stemming from a third party. Multiple users submit their ratings to a third party about items they have viewed. The third ...