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
With the recent outbreak of the COVID-19 pandemic, wearing face masks has become extremely important to protect us, and to reduce the spread of the virus. This measure has made many existing face recognition systems inef…
Spirulina platensis and other microalgae are now being considered in the different fields of research. It is due to the former’s endless potential let alone, its high protein content. That is why, a stable demand of micr…
Small and massively imbalanced datasets are long-standing problems on medical image classification. Traditionally, researchers use pre-trained models to solve these problems, however, pre-trained models typically have a…
Image Retrieval Systems (IRSs) are applications that allow one to retrieve images saved at any location on a network. Most IRSs make use of reverse lookup to find images stored on the network based on image properties su…
Every year thousands of lives pass away worldwide due to vehicle accidents, and the main reason behind this is the drowsiness in drivers. A drowsiness detection system will help to reduce this accident and save many live…
Now-a-days, computer systems are important for artificial vision systems to analyze the acquired data to realize crucial tasks, such as localization and navigation. For successful navigation, the robot must interpret the…
Clustering is a predominant technique used in image segmentation due to its simple, easy and efficient approach. It is very important for the analysis, extraction and interpretation of images; which makes it used in mult…
Hyperspectral image is well-known for the identification of the objects on the earth's surface. Most of the classifier uses the spectral features and does not consider the spatial features to perform the classification a…
This study aims to develop a novel web-based decision support system for diabetic retinopathy screening and classification of eye fundus images for medical officers. The research delivers diabetic retinopathy information…
People with motor disabilities face problems such as being able to move around independently, as well as having difficulties to take advantage of the technological tools developed for their rehabilitation. This research…
