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Objective: To generate synthetic Orthopantomograms (OPGs) using generative Artificial Intelligence (AI) models and to evaluate the realism of synthetic images through assessments by humans as well as AI models. Methodolo...

Generative Artificial Intelligence (GAI) is changing what can be done with Recommender Systems (RS) in e-commerce by allowing much more interactive, situationally aware, and highly tailored experiences for users. The pur...

Abstract Background The research shows the impact of land use forms and population density on the spatial variation of COVID-19 cases and deaths. Selected elements of land use that influence the number of COVID-19 cases ...

The Indonesian Robot Contest (KRI) is an event to develop creativity and enrich science and technology in the field of robotics. In KRI, there are several branch categories, one of which is the KRPAI (Indonesian Fire Fig...

Meta-optics have opened new possibilities for portable, high-performance microscopy, offering ultrathin and highly customizable wavefront control in scenarios where bulky optics limit adoption. Here, we use this capabili...

Stimulated Raman scattering (SRS) microscopy is a fast Raman imaging technique that combines the molecular specificity of vibrational spectroscopy with the high spatial resolution and speed of laser-scanning microscopy. ...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...

ABSTRACT As a government‐regulated public service, traffic signal control (TSC) requires reliable and transparent decision‐making. However, existing deep reinforcement learning (DRL) methods, despite improvements in ...

Abstract The importance of fear level detection in affective computing using physiological signals has not been extensively explored. Accurately detecting fear responses facilitates real-time emotional monitoring and imp...

ABSTRACT Background and Aims De novo drug design is the process of generating novel lead compounds that possess desirable pharmacological activities and optimal physicochemical properties for therapeutic development. In ...

The ripening stage of a fruit is a crucial determinant of its quality. Traditional assessment methods for fruit ripeness are often subjective, error-prone, and time-consuming. Therefore, numerous attempts are being made ...

Silicon photonics switches are emerging as a key technology for realizing energy-efficient networks, spanning from intra data center to wafer-scale interconnections. This review focuses on recent developments and prospec...

The relevance of this study lies in the impact of the information society on the development and changes in Oriental languages worldwide. The preservation of their cultural diversity and unique features depends largely o...

With the constant advancement of the smart grid, zero-day attack processes in Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) networks are also continually evolving. This study...

Abstract This study seeks to address persistent challenges in traditional music education, particularly the subjectivity inherent in assessment criteria and the frequent delays in feedback, by harnessing the capabilities...

Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a collection of training examples and learn th...

Images compression is a widely studied topic. Conventional situations offer variable compression ratios depending on the image in question and, in general, do not yield good results for images that are rich in tones. Thi...

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are t...

The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference system implemented in the framework of adaptive networks. By using a hybri...

In the first part of this paper, a regular recurrent neural network (RNN) is extended to a bidirectional recurrent neural network (BRNN). The BRNN can be trained without the limitation of using input information just up ...

Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In...

Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, improve on the previous best result in semant...

We propose a technique for producing `visual explanations' for decisions from a large class of Convolutional Neural Network (CNN)-based models, making them more transparent. Our approach - Gradient-weighted Class Activat...

We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented as a deep convolutional neural...