Aims To develop and validate DeepAdapter, a novel deep learning algorithm that integrates self-supervised learning (SSL) and unsupervised domain adaptation (UDA) to enhance model generalisability for ...

Few people have shaped modern artificial intelligence across as many dimensions as Andrej Karpathy, as a researcher, engineer and teacher. Over the past decade, he has been at the forefront of some of ...

Abstract: Cervical cancer is one of the most common causes of mortality among women globally. Development of accurate, interpretable and clinically deployable automated systems for detection of ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Accurate and automated fruit classification plays a vital role in modern agriculture but remains challenging due to the wide variability in fruit appearances. In this study, we propose a novel ...

This study introduces Popnet, a deep learning model for forecasting 1 km-gridded populations, integrating U-Net, ConvLSTM, a Spatial Autocorrelation module and deep ensemble methods. Using spatial ...

Computer vision has emerged as one of the most transformative areas of artificial intelligence, with deep learning models driving unprecedented advancements in both theoretical understanding and ...

Deep learning has revolutionised computer vision by enabling models to learn hierarchical feature representations directly from raw data. Convolutional neural networks (CNNs) form the backbone of many ...