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 deadly COVID-19 pandemic is currently sweeping the globe, and millions of people have been exposed to false information about the disease, its remedies, prevention, and origins. During such perilous times, the propag…
Driver decisions and behaviors are the major factors in on-road driving safety. Most significantly, traffic injuries and accidents are reduced using the accurate driver behavior monitoring system. However, the challenges…
It is critical to select the model that best fits the situation while analyzing the data. Many scholars on classification and regression issues have offered ensemble techniques on tabular data, as well as other approache…
Depletion of skin and muscle tone has a considerable impact on the appearance of the face, which is constantly evolving. Algorithms necessitate a large number of aging faces for this purpose. Another popular deep learnin…
These days, the Internet is subjected to a variety of attacks that can harm network devices or allow attackers to steal the most sensitive data from these devices. IoT environment provides new perspective and requirement…
Handwritten character recognition is the most critical and challenging area of research in image processing. A computer's ability to detect handwriting input from various original sources, such as paper documents, images…
Infertility is one of the diseases in which researchers are interested. Infertility disease is a global health concern, and andrologists are constantly looking for more advanced solutions for this disease. The intracytop…
The main objective of this work is to enhance the prediction of the Freezing of Gait (FoG) episodes for patients with Parkinson's Disease (PD). Thus, this paper proposes a hybrid deep learning approach that considers FoG…
Emotions are the essential parts that convey mean-ing to the interlocutors during social interactions. Hence, recog-nising emotions is paramount in building a good and natural affective system that can naturally interact…
A denial-of-service (DoS) attack is a coordinated attack by many endpoints, such as computers or networks. These attacks are often performed by a botnet, a network of malware-infected computers controlled by an attacker.…
