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In this paper, we propose a revised version of the semantic decoder for multi-label classification task in the spoken language understanding (SLU) pilot task of the Dialog State Tracking Challenge 5 (DSTC5). Our model concatenates two deep neural networks – a Convolutional Neural Network (CNN) and a Recurrent Neural Networks (RNN) – for detecting semantic…

Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…

As models based in artificial intelligence increase in sophistication, there is a higher demand for the integration of hardware components to heighten real-world implementations. Both facial feature tracking and shape-from-focus are known techniques in computer vision. However, the combination of these two elements, particularly in a cost-effective configuration, has not been extensively explored. In this…

As society ages, the imbalance between family caregivers and elderly individuals increases, leading to inadequate support for seniors in many regions. This situation has ignited interest in automatic health monitoring systems, particularly in fall detection, due to the significant health risks that falls pose to older adults. This research presents a vision-based fall detection system…

Cyber security is based on different principles such as confidentiality and integrity of transmitted data. One of the main methods to send confidential messages is to use a shared secret to encrypt and decrypt them. Even if the amortized computational complexity of the hashing functions is Ο(1), there are several situations when it is not…

Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…

An enduring vision of Artificial Intelligence is to build robots that can recognize and learn the visual world and who can speak about it in natural language. Automatic image description generation is a demanding problem in Computer Vision and Natural Language Processing. The applications of image description generation systems are in biomedicine, military, commerce, digital…

The ocean surface temperatures or sea surface temperatures have a significant influence on local and global weather. The change in sea surface temperatures will lead to the change in rainfall patterns. In this paper, the long-term rainfall forecasting is developed for planning and decision making in water resource management. The similarity of sea surface temperature…

An automatic speech recognition (ASR) is a key technology for preventing an ongoing global coronavirus epidemic. Due to the limited corpus database and the morphological diversity of the Thai language, Thai speech recognition is still difficult. In this research, the automatic speech recognition model was built differently from the traditional Thai NLP systems by using…

In recent days, the fast growth of populations leading to an increase in medically complicated cases, especially fast spread viral cases around the world. These phenomena increased demand on auto-diagnose systems to speed up the diagnosis process and reduce human contacts, especially for the COVID-19 pandemic using deep learning (DL). DL methods can successfully carry…

Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to the popularity of autonomous driving and traffic surveillance. In this work, the authors propose a multiple linear regression haze removal model based on a widely adopted dehazing algorithm named Dark Channel Prior. Training this…

Music Emotion Recognition (MER) is a study to recognize emotion in a music or song. MER is still challenging in the music world since recognizing emotion in music is affected by several features; audio is one of them. This paper uses a deep learning approach for MER, specifically Convolutional Neural Network (CNN) and Convolutional Recurrent…

Vehicle number plate detection and recognition is an integral part of the Intelligent Transport System (ITS) as every vehicle has a number plate as part of its identity. The quantity of vehicles on road is growing in the modern age, so numerous crimes are also increasing day by day. Almost every day the news of…

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…

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…

The paper treats a problem for detection and recognition objects in computer vision sector, where researchers recommended OpenCV software and development tool, it’s several and better-remembered library resource for isolating, detecting, and recognition of particular objects, what we would find an appropriate system for detecting and recognition traffic roads signs. The robustness with optimization is…

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…

Recognizing the human behavior and gesture has become important due to the increasing use of wearable devices. This study classifies hand gestures by creating sound in the inaudible frequency range from a smartphone and analyzing the reflected signals. We convert the sound using Short-Time Fourier Transform to magnitude and phase. We trained two types of…

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…

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…

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,…

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…

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…

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…

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…