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
Renal pathology represents a diverse set of diseases that present significant clinical relevance. Included among the various types of renal pathologies are renal stones, cysts, and renal malignancies, all of which requir…
As the volume of scientific information is growing exponentially in several languages, there is a need for practical and scalable bilingual classification systems for large aligned scientific text corpora. To address thi…
Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide, where early and accurate diagnosis plays a vital role in improving survival rates. Recent advancements in deep learning h…
Reconstructing the canonical pose of non-rigid objects from arbitrary depth observations is an important problem in robotic vision, particularly for systems that must perceive, track, and interact with deformable objects…
User-generated product reviews are an essential source of information in e-commerce; nevertheless, the huge volume and varying quality of review texts make extracting insights difficult. The conventional approach to sent…
Aspect-Based Sentiment Analysis (ABSA) aims to identify opinion targets within textual reviews and determine the sentiment polarity associated with each target. Although transformer-based models have significantly improv…
Breast cancer (BC) remains the leading cause of cancer-related death all over the world. Early accurate detection is key to the improvement of patient prognosis. The ability of advanced Artificial Intelligence (AI) metho…
This research provides a comprehensive synthesis of Multimodal Machine Learning (MML) as a transformative paradigm for IoT defense. By integrating heterogeneous data streams, including network flow statistics, device-lev…
Advancements in Artificial Intelligence (AI) technology have enabled the recognition of human emotions. Along with the development of deep learning and multimodal processing methods, emotion analysis can now be performed…
Deep learning (DL) is currently considered one of the most powerful tools for environmental monitoring. Many environmental variables, such as air quality, climate, water, and energy, are monitored using Internet of Thing…
