Πλοήγηση ανά Θέμα "Machine-learning"
Αποτελέσματα 1-20 από 28
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AI-driven Service-aware Real-time Slicing for beyond 5G Networks
(2022)Wide network softwarization is creating fertile ground for the application of novel concepts in the management of the deployed network functions. This allows a drastic shift for the applications hosted on top of the network, ... -
Artificial Intelligence, Big Data Analytics, and Smart Cities
(2022)Modern urban life is seeing an increasing rate of adoption of artificial intelligence and smart solutions; however, citizens are still struggling to keep up the pace, and the rate at which they acquire skills and knowledge ... -
Assessing Durum Wheat Yield through Sentinel-2 Imagery: A Machine Learning Approach
(2022)Two modeling approaches for the estimation of durum wheat yield based on Sentinel-2 data are presented for 66 fields across three growing periods. In the first approach, a previously developed multiple linear regression ... -
A Custom State LSTM Cell for Text Classification Tasks
(2022)Text classification is the task of assigning a class to a document. Machine Learning enables the automation of Text Classification Tasks, amongst others. Recent advances in the Machine Learning field, such as the introduction ... -
Deep Learning Models for Yoga Pose Monitoring
(2022)Activity recognition is the process of continuously monitoring a person’s activity and movement. Human posture recognition can be utilized to assemble a self-guidance practice framework that permits individuals to accurately ... -
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 ... -
Development of an electric car sharing system in a tourist area by using data driven tools: The idea of Erica project
(2022)Car sharing systems are an emerging solution aiming to reduce the widespread use of private vehicles and the negative effects that this entails. At the same time, the integration of electric vehicles into the fleet of car ... -
Distributed Fuzzy Cognitive Maps for Feature Selection in Big Data Classification
(2022)The features of a dataset play an important role in the construction of a machine learning model. Because big datasets often have a large number of features, they may contain features that are less relevant to the machine ... -
Elements of TinyML on Constrained Resource Hardware
(2022)The next phase of intelligent computing could be entirely reliant on the Internet of Things (IoT). The IoT is critical in changing industries into smarter entities capable of providing high-quality services and products. ... -
Forecasting Winter Precipitation based on Weather Sensors Data in Apache Spark
(2021)The proposed paper introduces an approach providing weather information on winter precipitation types using machine learning techniques. The proposed methodology takes as input the data received from weather sensors and ... -
Fuzzy Cognitive Maps for Interpretable Image-based Classification
(2022)Image classification is a fundamental component of intelligent vision systems. Developing classifiers capable of explaining how or why a classification result occurs, in a way compatible with human perception, remains a ... -
Hyper-parameters Tuning of Artificial Neural Networks: An Application in the Field of Recommender Systems
(2022)In this work, we carry out the hyper-parameters tuning of a Machine Learning (ML) Recommender Systems (RS) which utilizes an Artificial Neural Network (ANN), called CATA++. We have performed tuning of the activation function, ... -
Improving Hierarchical Short Text Clustering through Dominant Feature Learning
(2022)This paper focuses on the popular problem of short text clustering. Since the short text documents typically exhibit high degrees of data sparseness and dimensionality, the problem in question is generally considered more ... -
Leveraging Machine Learning for Gate-level Timing Estimation Using Current Source Models and Effective Capacitance
(2022)With process technology scaling, accurate gate-level timing analysis becomes even more challenging. Highly resistive on-chip interconnects have an ever-increasing impact on timing, signals no longer resemble smooth saturated ... -
MACHINE LEARNING to DEVELOP A MODEL THAT PREDICTS EARLY IMPENDING SEPSIS in NEUROSURGICAL PATIENTS
(2022)Sepsis is currently defined as a "life-threatening organ dysfunction caused by a dysregulated host response to infection". The early detection and prediction of sepsis is a challenging task, with significant potential gains ... -
Near Data Processing Performance Improvement Prediction via Metric-Based Workload Classification
(2022)Contrary to the improvement of CPU capabilities, traditional DRAM evolution faced significant challenges that render it the main performance bottleneck in contemporary systems. Data-Intensive applications such as Machine ... -
The next generation cognitive security operations center: Network flow forensics using cybersecurity intelligence
(2018)A Security Operations Center (SOC) can be defined as an organized and highly skilled team that uses advanced computer forensics tools to prevent, detect and respond to cybersecurity incidents of an organization. The ... -
Prediction of Injuries in CrossFit Training: A Machine Learning Perspective
(2022)CrossFit has gained recognition and interest among physically active populations being one of the most popular and rapidly growing exercise regimens worldwide. Due to the intense and repetitive nature of CrossFit, concerns ... -
Quantum Machine Learning: Current State and Challenges
(2021)In recent years, machine learning has penetrated a large part of our daily lives, which creates special challenges and impressive progress in this area. Nevertheless, as the amount of daily data is grown, learning time is ... -
Recent Dimensionality Reduction Techniques for High-Dimensional COVID-19 Data
(2022)We are going through the last years of the COVID-19 pandemic, where almost the entire research community has focused on the challenges that constantly arise. From the computational and mathematical perspective, we have to ...