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Keyword: Neural networkAmerican Sign Language Recognition Based on MobileNetV2
Sign language is a form of communication language designed to link a deaf-mute person to the world. To express an idea it requires the use of hand gestures and body movement. However, the bulk of the general population remain uneducated to understand the sign language. Therefore, a translator is required to facilitate the communication. This…
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 MoreEmotion Recognition on FER-2013 Face Images Using Fine-Tuned VGG-16
Facial emotion recognition is one among many popular and challenging tasks in the field of computer vision. Numerous researches have been conducted on this task and each proposed either standalone- or ensemble-based processing technique. While many researches strive for better accuracy, this research also attempts to increase the processing efficiency of computer correctly classifying human…
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 MoreEffective Segmented Face Recognition (SFR) for IoT
Face recognition technology becoming pervasive in the fields of computer vision, image processing, and pattern recognition. However, face recognition accuracy rates will decrease if training is done on disguised images with covered objects on a face area. This paper aims to propose a state-of-the-art face recognition methodology which could be applied in Internet of Things…
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 MoreA Proactive Mobile Edge Cache Policy Based on the Prediction by Partial Matching
The proactive caching has been an emerging approach to cost-effectively boost the network capacity and reduce access latency. While the performance of which extremely relies on the content prediction. Therefore, in this paper, a proactive cache policy is proposed in a distributed manner considering the prediction of the content popularity and user location to minimise…
Read MorePosture Recognition Method for Caregivers during Postural Change of a Patient on a Bed using Wearable Sensors
Caregivers experience lower back pain due to their awkward postures while handling patients. Therefore, a monitoring system to supervise caregivers’ postures using wearable sensors is being developed. This study proposed a postural recognition method for caregivers during postural change while handling a patient on a bed. The proposed method recognizes foot positions and arm movements…
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 MoreBISINDO (Bahasa Isyarat Indonesia) Sign Language Recognition Using CNN and LSTM
Sign language is one of the languages which are used to communicate with deaf people. By using it, they can communicate and understand each other. In Indonesia, there are two standards of sign language which are SIBI (Sistem Bahasa Isyarat) and BISINDO (Bahasa Isyarat Indonesia). Deep learning is a model that is used to apply…
Read MoreDifferential Evolution based Hyperparameters Tuned Deep Learning Models for Disease Diagnosis and Classification
With recent advancements in medical filed, the quantity of healthcare care data is increasing at a faster rate. Medical data classification is considered as a major research topic and numerous research works have been already existed in the literature. Presently, deep learning (DL) models offers an efficient method for developing a dedicated model to determine…
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 MoreReal-Time Traffic Sign Detection and Recognition System for Assistive Driving
Road traffic accidents are primarily caused by drivers error. Safer roads infrastructure and facilities like traffic signs and signals are built to aid drivers on the road. But several factors affect the awareness of drivers to traffic signs including visual complexity, environmental condition, and poor drivers education. This led to the development of different ADAs…
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 MoreThe Sound of Trust: Towards Modelling Computational Trust using Voice-only Cues at Zero-Acquaintance
Trust is essential in many interdependent human relationships. Trustworthiness is measured via the effectiveness of the relationships involving human perception. The decision to trust others is often made quickly (even at zero acquaintance). Previous research has shown the significance of voice in perceived trustworthiness. However, the listeners’ characteristics were not considered. A system has yet…
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 MoreComputational Intelligence and Statistical Learning Performances on Predicting Dengue Incidence using Remote Sensing Data
Dengue is a viral infection disease transmitted to people through the bite of specific mosquito species living in a tropical zone. According to the World Health Organization, dengue has been listed among the top-ten diseases for 2019 as it makes 3.9 billion people in 128 countries be at risk of infection. One major cause of…
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 MoreOffline Signature Recognition and Verification Using ORB Key Point Matching Techniques
An extensive work has been carried out in the field of human transcribe-verification and transcribe-recognition by extensive scholars across the globe from past decades. In order to demeanour immense experiments for considering the performance of the newly intended models and to substantiate the efficacy of the proposed model which is moderately required. This paper monologue…
Read MoreA Survey on Image Forgery Detection Using Different Forensic Approaches
Recently, digital image forgery detection is an emergent and important area of image processing. Digital image plays a vital role in providing evidence for any unusual incident. However, the image forgery my hide evidence and prevents the detection of such criminal cases due to advancement in image processing and availability of sophisticated software tamper of…
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