The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on deep learning — covering neural network architectures such as CNNs, RNNs, and transformers, and their applications across computer science domains.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
This paper research introduces a cutting-edge approach to enhancing urban infrastructure safety through the integration of modern technologies. Leveraging state of the art deep learning techniques, specifically the recen…
With the increasing demand for human-computer interaction and the development of emotional computing technology, facial expression recognition has become a major focus in research. In this paper, an improved VGG19 networ…
Esophageal cancer (EC) is a severe and commonly increasing disease due to the uncontrolled growth in the esophagus. It is the sixth leading cause of cancer-related deaths worldwide. The traditional methods for the diagno…
In today's cyber environment, modern botnets and malware are increasingly employing domain generation mechanisms to circumvent conventional detection solutions reliant on blacklisting or statistical methods for malicious…
People in areas affected by natural disasters and use social media websites such as Facebook, Twitter (also known as “X”) and Instagram tend to post images of damage to their surroundings. These social media sites have b…
Diabetic retinopathy (DR) is a leading cause of blindness worldwide, particularly among working-age individuals. With the increasing prevalence of diabetes, there is an urgent need to address the public health burden pos…
In 2023, Indonesia experienced an increase Industrial oil palm plantations grew by 116,000 hectares in 2023, an increase of 54% from the previous year. Oil palm is one of the main agricultural commodities in Indonesia, w…
This paper proposes a multi-scale asymmetric convolutional neural network (MACNN), specifically designed to tackle the challenges encountered by traditional convolutional neural networks in the realm of children's facial…
Vehicular Ad-hoc Networks (VANETs) are engineered to meet the distinctive demands of vehicular communication, facilitating interactions between vehicles and roadside infrastructure to enhance road safety, traffic efficie…
The volume and complexity of textual data have significantly increased worldwide, demanding a comprehensive understanding of machine learning techniques for accurate text classification in various applications. In recent…
