The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Deep learning is a subfield of machine learning built on artificial neural networks with multiple layers that automatically learn hierarchical representations of data, reducing the need for manual feature engineering. Architectures include convolutional neural networks for image and spatial data, recurrent neural networks and long short-term memory networks for sequential data, and transformer models, which now underpin most state-of-the-art natural language processing and increasingly computer vision systems. Training deep networks typically relies on large labeled datasets, backpropagation, and gradient-based optimization, along with regularization techniques and specialized hardware such as GPUs and TPUs. A notable 2026 shift in the field favors smaller, specialized models over ever-larger ones, prioritizing reliability, transparency, and efficient inference over raw parameter count. Deep learning drives advances in image recognition, speech processing, machine translation, medical image diagnosis, and generative models for text, images, and audio. As an open-access deep learning journal, IJACSA covers novel deep learning architectures and their evaluation across vision, language, and applied domains.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
Stroke detection from computed tomography (CT) images is an important research direction in computer vision. However, prior studies often use different preprocessing steps, model configurations, and evaluation protocols,…
This study presents an indoor vision-based fire detection system that integrates a YOLOv8n object detection model with a Reinforcement Learning-based Optimization Algorithm (ROA) for hyperparameter tuning. The research i…
Skin cancer is one of the fastest-growing health problems worldwide. Early and accurate diagnosis is essential for improving treatment success and patient survival. However, many previous studies have focused on single C…
Sleep posture is a critical factor affecting sleep quality and long-term health, particularly for the elderly and patients with chronic conditions. This research proposes a novel hybrid algorithm for real-time, vision-ba…
Detecting rare and subtle anomalies is critical for ensuring cybersecurity, financial integrity, and operational safety. High-dimensional features, severe class imbalance, and large data volumes often challenge conventio…
In the context of rapidly expanding urban water supply networks and the prevalence of pipe defects – for example, corrosion, cracks, leaks, blockages – that undermine efficiency and pose safety risks, this study presents…
Aiming at the traditional deep learning fall detection model due to high computational complexity and a large number of parameters, this study proposes a lightweight convolutional neural network model, SD-CNN (SMA-Enhanc…
The mental health of adult students is crucial not only for enhancing their learning experience and overall quality of life, but also for alleviating academic and employment-related anxiety. A significant challenge in de…
The global shift towards renewable energy has positioned wind power as a cornerstone of sustainable development. However, the operational efficiency of wind farms is significantly hampered by unexpected component failure…
The rapid evolution of generative adversarial networks (GANs) and diffusion models has made synthetic media increasingly realistic, raising societal concerns around misinformation, identity fraud, and digital trust. Exis…
