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
Image classification, a complex perceptual task with many real life important applications, faces a major challenge in presence of noise. Noise degrades the performance of the classifiers and makes them less suitable in…
Domotics is the study that involves the fusion of the words “domus” (which means home in latin) and “robotics”, linked directly to the act of automating something. Using facial recognition, by detecting the blink of eyes…
The artistic style of a painting can be sensed by the average observer, but algorithmically classifying the artistic style of an artwork is a difficult problem. The recently introduced neural-style algorithm uses feature…
A vehicle detection algorithm developed by Surendra (called Surendra algorithm) is composed of three parts: segmentation, adaptive background updating and background extraction. Surendra algorithm is sensitive to dynamic…
Secure signal processing is becoming a de facto model for preserving privacy. We propose a model based on the Fully Homomorphic Encryption (FHE) technique to mitigate security breaches. Our framework provides a method to…
Precision agriculture involves observing the crop production process and applying appropriate actions to improve production efficiency. In this paper, a smart vision system is developed to monitor specialty crops which i…
360 degrees surround photography or photospheres have taken the world by storm as the new media for content creation providing viewers rich, immersive experience compared to conventional photography. With the emergence o…
In this paper, we describe three different approaches for determining or finding a distance map for a binary image. The algorithms that solve such problems are known as Distance Transforms. These algorithms that solve su…
The proliferation of projection mapping and computer vision techniques have made it possible to create a multiplicity of dynamic, illuminated environments that adapt to user intervention. This paper describes a unique sy…
Shadow detection is the most important aspect in the field of image processing. It has become essential to develop such algorithms that are capable of processing the images with the maximum efficiency. Therefore, the res…
