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
Two key technologies in robotic object grasping are target object localization and pose estimation (PE), respectively, and the addition of a robotic vision system can dramatically enhance the flexibility and accuracy of…
In recent years, natural language processing (NLP) has transformed numerous domains, becoming a vital area of research. However, the focus of NLP studies has predomi-nantly centered on major languages like English, inadv…
Recognition of human intention is crucial and challenging due to subtle motion patterns of a series of action evolutions. Understanding of human actions is the foundation of many applications, i.e., human robot interacti…
This paper proposes a U-Net-based deep learning architecture for the task of super-resolution of lower resolution brain magnetic resonance images (MRI). The proposed system, called MRI-Net, is designed to learn the mappi…
One of the main functions of NLP (Natural Language Processing) is to analyze a sentiment or opinion of the text considered. In this research the objective is to analyze the sentiment in the form of tweets towards the Cov…
Deep learning methods have achieved significant success in various applications, including trend signal prediction in financial markets. However, most existing approaches only utilize price action data. In this paper, we…
Flowers are admired and used by people all around the world for their fragrance, religious significance, and medicinal capabilities. The accurate taxonomy of these flower species is critical for biodiversity conservation…
The novel human Corona disease (COVID-19) is a pulmonary sickness brought on by an extraordinarily outrageous respiratory condition crown 2. (SARS -CoV-2). Chest radiography imaging has a significant role in the screenin…
Delay-Tolerant Networking (DTN) or Disruptive-Tolerant Networking comes under the category of networks that works without infrastructure wireless networks. DTN is one type of computer network that provides solutions for…
In Brain-Computer interface (BCI) applications, achieving accurate control relies heavily on the classification accuracy and efficiency of motor imagery electroencephalogram (EEG) signals. However, factors such as mutual…
