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
Corn has particular importance in the global food industry. Many diseases attack the corn crops, which affects the crop yield. Early classification and detection of these diseases are pivotal to preventing damage and ach…
Breast cancer has been listed as one of the leading causes of death amongst women all over the world, and the current diagnostic techniques, which are founded on the manual examination of mammograms or individual clinica…
This study presents the design, development, and evaluation of an intelligent fruit-picking robot that integrates convolutional vision, adaptive gripping mechanisms, and kinematic control to enable automated harvesting i…
South Sumatra songket motifs present a challenging fine-grained classification task due to high inter-class similarity and substantial intra-class variability. This study proposes the Ghost-Vanilla Feature Map, a novel h…
Non-invasive neural speech interfaces aim to reconstruct intended words from brain activity, offering critical communication options for individuals with severe dysarthria or locked-in syndrome. Among the available recor…
The increasing digitization in banking and related financial services has resulted in spurring the level of transactions with fraudulent patterns and thus demands detection solutions not only efficient but also interpret…
Driver drowsiness is a major cause of traffic accidents, so Edge-IoT platforms with limited resources need to be able to accurately and quickly detect when drivers are drowsy. This study examines attention-guided lightwe…
Deep learning (DL) has become a transformative approach in medical image analysis, offering superior accuracy and automation in image segmentation tasks. In reproductive imaging, transvaginal ultrasound (TVUS) serves as…
The accelerated growth of digital content and the increasing presence of emotional expressions, polarized opinions, and toxic behaviors in social media have driven the development of advanced Affective Analysis technique…
Dentistry is a medical branch that diagnoses and treats oral diseases, helps maintain oral function, and improves oral aes-thetics. Dental casts are three-dimensional models of a patient’s oral tissues that can be used t…
