The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Computer vision is the field of artificial intelligence concerned with enabling computers to interpret and extract information from visual data such as images and video. Core tasks include image classification, object detection and localization, semantic and instance segmentation, facial recognition, and optical character recognition. Early approaches relied on hand-crafted feature descriptors combined with classical machine learning classifiers; current computer vision is dominated by convolutional neural networks and, increasingly, vision transformer architectures trained on large annotated image datasets. A notable 2026 development is the shift toward foundation models that displace task-specific training for many commercial applications, alongside growing use of agentic vision systems moving from research into operational deployment. Computer vision supports applications including autonomous vehicle perception, medical image analysis, industrial quality inspection, surveillance and security systems, and augmented reality. As an open-access computer vision journal, IJACSA publishes research on computer vision algorithms, model architectures, and applied vision systems evaluated on standard and domain-specific image datasets.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
Over the past years, clients have largely depended on and trusted Automated Teller Machines (ATMs) to fulfill their banking needs and control their accounts easily and quickly. Despite the significant advantages of ATMs,…
The sky depicts a high visual importance in outdoor scenes, often appearing in video sequences and photos. Sky information is crucial for accurate sky detection in several computer vision applications, such as scene unde…
Aiming at the problem that improper posture of basketball players leads to not obvious sports effects, the present paper proposes an action recognition method combining computer vision and big data technology and applies…
In light of the explosive growth of drones, it is more critical than ever to strengthen and secure aerial security and privacy. Drones are used maliciously by exploiting some gaps in artificial intelligence and cybersecu…
Monitoring rice spikelet yield is crucial for ensuring food security, but manual observations are tedious and subjective. Deep learning approaches for automated counting often require high device resources, limiting thei…
Human Action Recognition and Medical Image Segmentation study presents a novel framework that leverages advanced neural network architectures to improve Medical Image Segmentation and Human Action Recognition (HAR). Gate…
In the field of orthodontics, the accurate identification of cephalometric landmarks in dental radiography plays a crucial role in ensuring precise diagnoses and efficient treatment planning. Previous studies have demons…
This paper addresses the challenge of accurately detecting and recognizing Arabic license plates, particularly those subjected to severe tilt angles. It presents a robust license plate detection and recognition framework…
Ischemic stroke is the most prevalent type of stroke and a leading cause of mortality and long-term impairment globally. Timely identification, precise localization, and early detection of ischemic stroke lesions brain a…
Smart health houses have shown great potential for providing advanced healthcare services and support to individuals. Although various computer vision based approaches have been developed, current facial expression analy…
