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 October 2026
In recent years, accidents involving slide playground equipment have frequently occurred due to various reasons, attracting significant attention. Reducing or even eliminating these accidental injuries has become an urge…
Climate change is one of the most talked-about topics of this decade, affecting all economic output sectors, including the economy of cow farming. In many scenarios, exceptionally severe climate change is predicted for t…
Facial recognition is widely used in security and identification systems, but occlusions like masks or glasses remain a major challenge. Recent approaches, such as GANs and partial feature extraction methods, attempt to…
The development of Internet and Internet of things technology has accelerated the informatization construction of smart education. But the traditional face recognition algorithm used in smart classrooms inevitably has pr…
Small object detection has many applications, including maritime surveillance, underwater computer vision, agriculture, traffic flow analysis, drone surveying, etc. Object detection has made notable improvements in recen…
Makkah, one of the most significant cities in the Islamic world, possesses a rich architectural and cultural heritage that requires precise detection and identification of its landmarks. Accurate landmark detection plays…
Floods are among the most frequent and devastating natural disasters, significantly impacting infrastructure, ecosystems, and human communities. Accurate satellite-based flood image classification is crucial for assessin…
Air pollution poses significant threats to human health and the environment, making effective monitoring increasingly essential. Traditional methods using fixed monitoring stations have challenges related to high costs a…
The high prevalence of cellphones and social networking platforms such as Snapchat are obviously dissolving traditional barriers between information providers and end-users. It is certainly relevant in emergency events,…
This study evaluates the performance of deep learning-based segmentation models applied to underwater images for scallop aquaculture in Sechura Bay, Peru. Four models were analyzed: SUIM-Net, YOLOv8, DETECTRON2, and Cent…
