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
Segmentation, as a preprocessing, plays an important role in hyperspectral images. In this paper, considering the similarity of neighboring pixels, using the size measure, the image spectrum is divided into several segme…
In this paper, a fully automatic 2.5D facial technique for forensic applications is presented. Feature extraction and classification are fundamental processes in any face identification technique. Two methods for feature…
Deep learning system is used for solving many problems in different domains but it gives an over-fitting risk when richer representations are increased. In this paper, three different models with different deep multiple…
This paper proposes two optimal Cordic Loeffler based DCT (Discrete Cosine Transform algorithm) architectures: a fast and low Power DCT architecture and a high PSNR DCT architecture. The rotation parameters of CORDIC ang…
QR (Quick Response) code recognition systems (based on computer vision) have always been challenging to be accurately devised due to two main constraints: (1) QR code recognition system must be able to localize QR codes…
Tumor segmentation inside the brain MRI is one of the trickiest and demanding subjects for the research community due to the complex nature and structure of the human brain and the different types of abnormalities that g…
Facial expression is complex in nature due to legion of variations present. These variations are identified and recorded using feature extraction mechanisms. The researchers have worked towards it and created classifiers…
Recording, storing and sharing video content has become one of the most popular usages of smartphones. This has resulted in demand for video editing apps that the users can use to edit their videos before sharing on vari…
Medical image processing is one of the most demanding domains of the computing sciences. The importance of the domain is in terms of the CPU and the memory requirements that shall be used by the system to compute the res…
The face recognition applications are widely used in different fields like security and computer vision. The recognition process should be done in real time to take fast decisions. Princi-ple Component Analysis (PCA) con…
