The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on deep learning — covering neural network architectures such as CNNs, RNNs, and transformers, and their applications across computer science domains.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
This paper demonstrates a computer-aided diagnosis (CAD) system for lung cancer classification of CT scans with unmarked nodules, a dataset from the Kaggle Data Science Bowl, 2017. Thresholding was used as an initial seg…
Differentiating melanocytic from non-melanocytic (MnM) skin lesions is the first and important step required by clinical experts to automatically diagnosis pigmented skin lesions (PSLs). In this paper, a new clinically-o…
In this paper, a framework has been presented by using a combination of deep Convolutional Neural Network (CNN) with Support Vector Machine (SVM). Proposed method first perform preprocessing to resize the image so that i…
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…
Advancement in deep unsupervised learning are finally bringing machine learning close to natural learning, which happens with as few as one labeled instance. Ladder Networks are the newest deep learning architecture that…
Detection of glaucoma eye disease is still a challenging task for computer-aided diagnostics (CADx) systems. During eye screening process, the ophthalmologists measures the glaucoma by structure changes in optic disc (OD…
The World Wide Web such as social networks, forums, review sites and blogs generate enormous heaps of data in the form of users views, emotions, opinions and arguments about different social events, products, brands, and…
In Bioinformatics, Protein Secondary Structure Prediction (PSSP) has been considered as one of the main challenging tasks in this field. Today, secondary structure protein prediction approaches have been categorized into…
Puzzles and board games represent several important classes of AI problems, but also represent difficult complexity classes. In this paper, we propose a deep learning based alternative to train a neural network model to…
Medical Image Fusion (MIF) can improve the performance of medical diagnosis, treatment planning and image-guided surgery significantly through providing high-quality and rich-information medical images. Traditional MIF t…
