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Keyword: Neural networksEnvironmental Acoustics Modelling Techniques for Forest Monitoring
Environmental sounds detection plays an increasing role in computer science and robotics as it simulates the human faculty of hearing. It is applied in environment research, monitoring and protection, by allowing investigation of natural reserves, and showing potential risks of damage that can be deduced from the environmental acoustic. The research presented in this paper…
Read MoreDevelopment of an EEG Controlled Wheelchair Using Color Stimuli: A Machine Learning Based Approach
Brain-computer interface (BCI) has extensively been used for rehabilitation purposes. Being in the research phase, the brainwave based wheelchair controlled systems suffer from several limitations, e.g., lack of focus on mental activity, complexity in neural behavior in different conditions, and lower accuracy. Being sensitive to the color stimuli, the EEG signal changes promises a better…
Read MoreA-MnasNet and Image Classification on NXP Bluebox 2.0
Computer Vision is a domain which deals with the challenge of enabling technology with vision capabilities. This goal is accomplished with the use of Convolutional Neural Networks. They are the backbone of implementing vision applications on embedded systems. They are complex but highly efficient in extracting features, thus, enabling embedded systems to perform computer vision…
Read MoreClassifying Garments from Fashion-MNIST Dataset Through CNNs
Online fashion market is constantly growing, and an algorithm capable of identifying garments can help companies in the clothing sales sector to understand the profile of potential buyers and focus on sales targeting specific niches, as well as developing campaigns based on the taste of customers and improve user experience. Artificial Intelligence approaches able to…
Read MoreText Mining Techniques for Cyberbullying Detection: State of the Art
The dramatic growth of social media during the last years has been associated with the emergence of a new bullying types. Platforms such as Facebook, Twitter, YouTube, and others are now privileged ways to disseminate all kinds of information. Indeed, communicating through social media without revealing the real identity has emerged an ideal atmosphere for…
Read MoreComparison of Machine Learning Parametric and Non-Parametric Techniques for Determining Soil Moisture: Case Study at Las Palmas Andean Basin
Soil moisture is one of the most important variables to monitor in agriculture. Its analysis gives insights about strategies to utilize better a particular area regarding its use, i.e., pasture for cows (or similar), production forests, or even to answer what crops should be planted. The vertical structure of the soil moisture plays an important…
Read MoreTechnological Stages of Schwartz Cylinder’s Computer and Mathematics Design using Intelligent System Support
In this paper, one of the “problem zones” in mathematics concerned with the surface area of three-dimensional bodies is presented by computer and mathematical modeling with synergetic effects using intelligent system support. The problems of personal self-organization and technological stages of student’s research activity in the process of modern achievements in science adaptation in teaching…
Read MoreStandardized UCI-EGO Dataset for Evaluating 3D Hand Pose Estimation on the Point Cloud
To evaluate and compare methods in computer vision, scientists must use a benchmark dataset and unified sets of measurements. The UCI-EGO dataset is a standard benchmark dataset for evaluating Hand Pose Estimation (HPE) on depth images. To build robotic arms that perform complex operations such as human hands, the poses of the human hand need…
Read MoreElectronic Warfare Methods Combatting UAVs
This paper describes methods of eliminating Unmanned Aerial Vehicles (UAV) non-destructively, using Electronic Warfare Methods. The aim is to introduce certain methods of UAV detection and elimination in a complex environment and terrain, e.g., in an urban and battlefield environment, that will result in finding the control device position and the UAV itself. Neural networks,…
Read MoreReal-Time Identification and Classification of Driving Maneuvers using Smartphone
The fast-paced development of smart technologies and the prevalence of vehicles, created an urgent demands to study and improve safety issues related to driving. In order to reduce traffic accidents, driving behavior was found to be very important issues to study and investigate. Recently, the advent and widespread of smartphone platforms with advanced computing competence…
Read MoreA Toolkit for the Automatic Analysis of Human Behavior in HCI Applications in the Wild
Nowadays, smartphones and laptops equipped with cameras have become an integral part of our daily lives. The pervasive use of cameras enables the collection of an enormous amount of data, which can be easily extracted through video images processing. This opens up the possibility of using technologies that until now had been restricted to laboratories,…
Read MoreInteractive Virtual Rehabilitation for Aphasic Arabic-Speaking Patients
Objective: Individuals with aphasia often experience significant problems in their daily lives and social participation. Technologies that address speech and language disorders deficit in merging between therapist’s major role and reinforcing the training between sessions at home. It also lacks the Arabic language attention; however, current systems are typically expensive and lack amusement. Moreover, cumulative…
Read MoreClassification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models
This article discusses the problem of handwriting recognition in Kazakh and Russian languages. This area is poorly studied since in the literature there are almost no works in this direction. We have tried to describe various approaches and achievements of recent years in the development of handwritten recognition models in relation to Cyrillic graphics. The…
Read MoreInvestment of Classic Deep CNNs and SVM for Classifying Remote Sensing Images
Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this…
Read MoreCNN-LSTM Based Model for ECG Arrhythmias and Myocardial Infarction Classification
ECG analysis is commonly used by medical practitioners and cardiologists for monitoring cardiac health. A high-performance automatic ECG classification system is a challenging area because there is difficulty in detecting and clustering various waveforms in the signal, especially in the manual analysis of electrocardiogram (ECG) signals. In this paper, an accurate (ECG) classification and monitoring…
Read MoreAdvances in Optimisation Algorithms and Techniques for Deep Learning
In the last decade, deep learning(DL) has witnessed excellent performances on a variety of problems, including speech recognition, object recognition, detection, and natural language processing (NLP) among many others. Of these applications, one common challenge is to obtain ideal parameters during the training of the deep neural networks (DNN). These typical parameters are obtained by…
Read MoreA Method for Detecting Human Presence and Movement Using Impulse Radar
Using non-invasive and non-contact sensors to measure a person’s presence or movement helps improve the quality of life for both healthy people and patients. In this paper, a method of measuring the presence and motion of a person is proposed by utilizing UWB Impulse Radar, which is low power consumption and safe to radiate to…
Read MoreHuman-Robot Multilingual Verbal Communication – The Ontological knowledge and Learning-based Models
In their verbal interactions, humans are often afforded with language barriers and communication problems and disabilities. This problem is even more serious in the fields of education and health care for children with special needs. The use of robotic agents, notably humanoids integrated within human groups, is a very important option to face these limitations.…
Read MoreArtificial Intelligence Approach for Target Classification: A State of the Art
The classification of static or mobile objects, from a signal or an image containing information as to their structure or their form, constitutes a constant concern of specialists in the electronic field. The remarkable progress made in past years, particularly in the development of neural networks and artificial intelligence systems, has further accentuated this trend.…
Read MoreA CNN-based Differential Image Processing Approach for Rainfall Classification
With the aim of preventing hydro-geological risks and overcoming the problems of current rain gauges, this paper proposes a low-complexity and cost-effective video rain gauge. In particular, in this paper the authors propose a new approach to rainfall classification based on image processing and video matching process employing convolutional neural networks (CNN). The system consists…
Read MoreDeep Learning Model for A Driver Assistance System to Increase Visibility on A Foggy Road
For many years, a lot of researches have been made to develop Advanced Driver Assistance Systems (ADAS) that are based on integrated systems. The main objective is to help drivers. Hence, keeping them safe under different driving conditions. Visibility for drivers remains the biggest problem faced on the road in an atmosphere of fog. In…
Read MoreTransfer Learning and Fine Tuning in Breast Mammogram Abnormalities Classification on CBIS-DDSM Database
Breast cancer has an important incidence in women mortality worldwide. Currently, mam- mography is considered the gold standard for breast abnormalities screening examinations, since it aids in the early detection and diagnosis of the illness. However, both identification of mass lesions and its malignancy classification is a challenging problem for artificial intelligence. In this work,…
Read MoreMulti Biometric Thermal Face Recognition Using FWT and LDA Feature Extraction Methods with RBM DBN and FFNN Classifier Algorithms
Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…
Read MoreImprove the Accuracy of Short-Term Forecasting Algorithms by Standardized Load Profile and Support Regression Vector: Case study Vietnam
Short-term load forecasting (STLF) plays an important role in building business strategies, ensuring reliability and safe operation for any electrical system. There are many different methods, including: regression models, time series, neural networks, expert systems, fuzzy logic, machine learning and statistical algorithms used for short-term forecasts. However, the practical requirement is how to minimize the…
Read MoreA Relation Extraction System for Indian Languages
Relation Extraction is an important subtask of Information Extraction that involves extracting significant facts from natural language text. Extracting structured information from the plaintext is the ultimate goal of IE systems. The Indian language content on the internet is increasing day to day. Extracting relevant information from this huge unstructured data is a challenging task…
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