The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on computer vision — including object detection, image classification, face recognition, and image segmentation techniques and applications.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
Breast cancer affects 1 in 8 women in the United States. Early detection and diagnosis is key to recovery. Computer-Aided Detection (CAD) of breast cancer helps decrease morbidity and mortality rates. In this study we ap…
The majority of manufacturers demand increasingly powerful vision systems for quality control. To have good outcomes, the installation requires an effort in the vision system tuning, for both hardware and software. As ti…
The major challenge in content based image retrieval is the semantic gap. Images are described mainly on the basis of their numerical information, while users are more interested in their semantic content and it is reall…
People are usually identified by their faces. Developments in the past few decades have enabled human to automatically do the identification process.Now, face recognition process employs the advanced statistical science…
This paper introduces a novel weighted unsuper-vised learning for object detection using an RGB-D camera. This technique is feasible for detecting the moving objects in the noisy environments that are captured by an RGB-…
The segmentation of image is considered as a significant level in image processing system, in order to increase image processing system speed, so each stage in it must be speed reasonably. Fuzzy c-mean clustering is an i…
This paper presents Evaluation K-mean and Fuzzy c-mean image segmentation based Clustering classifier. It was followed by thresholding and level set segmentation stages to provide accurate region segment. The proposed st…
In modern sciences and technologies, images gain much broader scopes due to the ever growing importance of scientific visualization (of often large-scale complex scientific/experimental data) like microarray data in gene…
This paper elaborates on the possibility to leverage the highly parallel nature of GPUs to implement more efficient stereo matching algorithms. Different algorithms have been implemented and compared on the CPU and the G…
The training optimization processes and efficient fast classification are vital elements in the development of a convolution neural network (CNN). Although stochastic gradient descend (SGD) is a Prevalence algorithm used…
