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
Face Recognition has progressed tremendously from its initial use of holistic learning models to using hand-crafted, shallow, and deep learning models. DeepFace, a nine-layer Deep Convolutional Neural Network (DCNN), rea…
Biomedical imaging is a rapidly evolving field that covers different types of imaging techniques which are used for diagnostic and therapeutic purposes. It plays a vital role in diagnosis and treating health conditions o…
Skin diseases are a global health problem that is difficult to diagnose sometimes due to the disease’s complexity, and the time-consuming effort. In addition to the fact that skin diseases affect human health, it also af…
In this paper, we improve the performance of Deep Learning (DL) by creating a robust and efficient Convolutional Neural Network (CNN) model. This CNN model will be subjected to detecting and recognizing traffic signs in…
Object recognition method is a computer vision technique for identifying objects in images. The main purpose of this system build is to put an end to blindness by constructing automated hardware with Raspberry Pi that en…
A removal nasogastric (NG) tube of a patient is a critical problem especially the patients resist swallowing. To solve this problem, the conventional approach using a personal caretaker is a time-consuming and intense fo…
As businesses move towards more customer-centric business models, marketing functions are becoming increasingly interested in gathering natural, unbiased feedback from cus-tomers. This has led to increased interest in co…
Since ancient times, natural fibers have been essential in paper production and packaging fabrication. However, beauty-marring carbonization, or a heat-affected zone (HAZ) generated during the laser cutting process of pa…
This paper proposes an approach that leverages real-time Image Classification to improve elevator safety. Elevators are a necessity for most multi story buildings. As a result, they play a crucial role in the lives of mi…
Object detection and classification denotes one of the most extensively-utilized machine vision applications given the high requirements put forward for object classification and defect detection with the rise of object…
