The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Deep learning is a subfield of machine learning built on artificial neural networks with multiple layers that automatically learn hierarchical representations of data, reducing the need for manual feature engineering. Architectures include convolutional neural networks for image and spatial data, recurrent neural networks and long short-term memory networks for sequential data, and transformer models, which now underpin most state-of-the-art natural language processing and increasingly computer vision systems. Training deep networks typically relies on large labeled datasets, backpropagation, and gradient-based optimization, along with regularization techniques and specialized hardware such as GPUs and TPUs. A notable 2026 shift in the field favors smaller, specialized models over ever-larger ones, prioritizing reliability, transparency, and efficient inference over raw parameter count. Deep learning drives advances in image recognition, speech processing, machine translation, medical image diagnosis, and generative models for text, images, and audio. As an open-access deep learning journal, IJACSA covers novel deep learning architectures and their evaluation across vision, language, and applied domains.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
The breakthroughs in securing speaker verification systems have been challenging and yet are explored by many researchers over the past five years. The compromise in security of these systems is due to naturally sounding…
Social media content in regional languages is ex-panding from day to day. People use different social media platforms to express their suggestions and thoughts in their native languages. Sentiment Analysis (SA) is the kn…
Malware, a short name for malicious software is an emerging cyber threat. Various researchers have proposed ways to build advanced malware detectors that can mitigate threat actors and enable effective cybersecurity deci…
Eye movement analysis has gained significant atten-tion from the eye-tracking research community, particularly for real-time applications. Eye movement prediction is predominantly required for the improvement of sensor l…
The main purpose of this work is to propose a robust approach for dangerous sound events detection (e.g. gunshots) to improve recent surveillance systems. Despite the fact that the detection and classification of differe…
Network security has become a serious issue since networks are vulnerable and subject to increasing intrusive activities. Therefore, network intrusion detection systems (IDSs) are an essential component to defend against…
The growing and marketing of coffee is an impor-tant source of economic resources for many countries, especially those with economies dependent on agricultural production, as is the case of Colombia. Although the country…
It is common among security organizations to run processes system call trace data to predict its anomalous behavior, and it is still a dynamic study region. Learning-based algorithms can be employed to solve such problem…
Now-a-days people use social media websites for different activities such as business, entertainment, following the news, expressing their thoughts, feelings, and much more. This initiated a great interest in analyzing a…
This article presents a framework for physical internet hubs inbound containers forecasting based on deep learning and time series analysis. The inbound containers forecasting is essential for planning, scheduling, and r…
