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
Humanity's survival, development, and existence are deeply intertwined with agriculture, the source of most of our food. Plant disease detection helps in securing food, but manual plant disease detection is error-prone a…
Early and accurate fault diagnosis in power distribution systems is essential to ensure stable electricity delivery and prevent outages. This study presents a deep learning-based anomaly detection framework that analyzes…
This study presents a hybrid deep learning approach for automated detection of bubbles in contact lenses, aiming to enhance quality assurance in the manufacturing process. A hybrid AlexNet+SVM model was developed using t…
Automated Essay Scoring (AES) has become a critical tool for scaling writing assessment in modern education. However, existing AES models often struggle to effectively evaluate both the syntactic structure and semantic m…
Many existing systems struggle to strike a balance between global feature discrimination and local semantic understanding, despite the growing popularity of Self-Supervised Learning (SSL) for representation learning with…
As cyber-attacks get increasingly sophisticated, cybersecurity threats have surged, with 430 million new malware instances identified in 2023 representing a 36% rise compared to 2020 figures in the United States.Traditio…
Wood anatomical features are crucial in forestry science, traditionally relying on manual inspection of wood cross-sections. This conventional method is time-consuming, subjective, and dependent on expert experience. Rec…
With the advancement of industrialization, air pollution has emerged as a critical global health and environmental concern. This study presents an air quality prediction model based on variational mode decomposition, a c…
This research introduces an advanced image encryption framework addressing critical security limitations in existing approaches. The study focuses on developing a robust encryption methodology that overcomes arbitrary ch…
The COVID-19 pandemic has profoundly impacted economic and social structures, directly affecting individuals’ lives. Deep learning models offer the potential to forecast future long-term trends and capture the temporal d…
