The Internet of Things (IoT) ecosystem connects physical devices to the internet, offering
significant advantages in agility, responsiveness, and potential environmental benefits. The …

Feature attributions based on the Shapley value are popular for explaining machine
learning models. However, their estimation is complex from both theoretical and …

Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

Ongoing improvements in AI, particularly concerning deep learning techniques, are
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …

Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

Artificial intelligence (AI) can extract visual information from histopathological slides and
yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of …

Effective fusion of global and local multi-scale features is crucial for medical image
classification. Medical images have many noisy, scattered features, intra-class variations …

Computer-aided detection using Deep Learning (DL) and Machine Learning (ML) shows
tremendous growth in the medical field. Medical images are considered as the actual origin …

Recently, artificial intelligence (AI) and blockchain have become two of the most trending
and disruptive technologies. Blockchain technology has the ability to automate payment in …

Abstract Nowadays, Deep Learning is the most attractive research trend in the area of
Machine Learning. With the ability of learning features from raw data by deep architectures …