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
The industrial sensors of IoT is an emerging model, which combines Internet and the industrial physical smart objects. These objects belong to the broad domains like the smart homes, the smart cities, the processes of th…
Intelligent transport system (ITS) is the development direction of future transport systems, in which intelligent vehicles are the key components. In order to protect the safety of intelligent vehicles, machine learning…
Towards malicious activity monitoring in organizations, there exist several techniques and suffer with poor accuracy. To handle this issue, an efficient Sketch and Size orient malicious activity monitoring (SSMAM) is pre…
Dance pose recognition and prediction is an important part of dance training and a challenging task in the field of artificial intelligence. Due to the diverse styles and significant variations in dance movements, conven…
Alzheimer's disease (AD) causes damage to brain cells and their activities. This disease is typically caused by ageing, making people over the age of 65 more susceptible. As the disease progresses, it slowly destroys bra…
Melanoma, the most severe type of skin cancer, ranks ninth among the most prevalent cancer types. Prolonged exposure to ultraviolet radiation triggers mutations in melanocytes, the pigment -producing cells responsible fo…
Effective and precise methodologies for evaluating the proficiency in English language instruction are instrumental in enhancing educators' competencies and the effectiveness of educational administrative processes. The…
This study introduces the MSTA-GNet (Multi-Scale Spatiotemporal Attention Graph Network), a novel deep learning model which integrates spatiotemporal self-attention mechanisms to model heterogeneous dependencies in traff…
Small proteins encoded by small open reading frames (sORFs) exhibit significant biological activity in crucial biological processes such as embryonic development and metabolism. Accurately predicting whether sORFs encode…
Humans use voice, gestures, and emotions to communicate with one another. It improves oral communication effectiveness and facilitates concept of understanding. Majority of people are able to identify facial emotions wit…
