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
Nowadays, pest infestations cause significant reductions in agricultural productivity all over the world. To control pests, farmers often apply excessive volumes of pesticides due to the difficulty of manually detecting…
During driving, drivers often overlook the traffic signs along the roads compromising road safety and increasing the risk of accidents. To address this, artificial intelligence (AI) and deep learning techniques are emplo…
Advanced deep-learning approaches have set new standards for computer vision and pattern recognition. However, the complexity of medical images frequently impedes the creation of high-quality ground truth data. In this a…
The detection of diabetic retinopathy traditionally requires the expertise of medical professionals, making manual detection both time- and labor-intensive. To address these challenges, numerous studies in recent years h…
Road surface crack detection is a critical task in road maintenance and safety management. Cracks in road surfaces are often the early indicators of larger structural issues, and if not detected and repaired in time, the…
Object detection is a fundamental task in gesture recognition, involving identifying and localising human hand or body gestures within images or videos amidst varying environmental conditions. To address the inadequate r…
Image enhancement is one of the most important areas that is being developed in the field of image processing technology. Image contrast enhancement can significantly improve the perception of the digital image itself. X…
The Philippines is the second largest producer of coconut products in the world with 347 million trees planted in 3.6 million hectares of land across the country. Traditionally, harvesting coconuts is a labor-intensive p…
This study explores the application of image recognition technology based on Convolutional Neural Network (CNN) to classify Lampung batik motifs. Four CNN architectures are employed, namely AlexNet, EfficientNet, LeNet,…
Detecting and regulating compliance at substation construction sites is critical to ensure the safety of workers. The complex backgrounds and diverse scenes of construction sites, as well as the variations in camera angl…
