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
The image compression techniques are the fast-growing methods and have developed on large scale. Among them, wavelet-based compression methods are most promising and efficient techniques widely used in the field of medic…
Wayang, an ancient cultural tradition in Java, has been an integral part of Indonesian culture for 1500 years. Rooted in Hindu cultural influences, wayang has evolved into a highly esteemed and beloved performance art. I…
A method for hyperparameter tuning of image classification with PyCaret is proposed. The application example compares 14 classification methods and confirms that Extra Trees Classifier has the best performance among them…
The work of the Ophthalmologist in manually detecting specific eye related disease is challenging especially screening through large volume of dataset. Deep learning models can leverage on medical imaging like the retina…
Due to diverse backdrops, scale fluctuations, and a lack of annotated training data, the identification and recognition of objects in remote sensing images present major problems. In order to overcome these difficulties,…
The use of submarine cables as underwater transmission channels for distributing electrical energy in Indonesian waters is crucial. However, the detection and maintenance of submarine cables still heavily rely on human o…
This paper presents a novel approach to fingerspelling recognition in real-time, utilizing a two-dimensional Convolutional Neural Network (2D CNN). Existing recognition systems often fall short in real-world conditions d…
Optimizing image processing parameters is often a time-consuming and unreliable task that requires manual adjustments. In this paper, we present a novel approach that utilizes a multi-agent system with Hysteretic Q-learn…
Using image processing technology has become increasingly essential in the education sector, with universities and educational institutions exploring innovative ways to enhance their teaching techniques and provide a bet…
Fast and accurate detection technology for individual pigs raised in herds is crucial for subsequent research on counting and disease surveillance. In this paper, we propose an improved lightweight object detection metho…
