This article discusses the use of deep learning models in multisource remote sensing data fusion and classification. It highlights the challenges faced by traditional…
Browsing: Transfer Learning
This article explores the concept of pre-trained models and their applications in text, image, and robotics domains. It discusses the benefits of pre-trained models,…
This article discusses the potential of deep transfer learning architectures to improve the accuracy of brain tumor diagnosis using machine vision. Four distinct architectures…
A study published in Engineering presents a hybrid aerosol retrieval algorithm for a geostationary meteorological satellite. The algorithm utilizes deep learning and transfer learning…
A study published in Engineering introduces a hybrid aerosol retrieval algorithm that combines deep learning and transfer learning to address challenges in traditional physical…
NXP Semiconductors and NVIDIA have collaborated to integrate NVIDIA’s TAO APIs into NXP’s eIQ machine learning development environment, making it easier for developers to…
This article discusses the use of transfer learning and explainable artificial intelligence (XAI) to accurately classify kidney-ureter-bladder (KUB) X-ray images as either normal or…
Transfer Learning is a machine learning paradigm that repurposes pre-trained models for new tasks, leveraging knowledge gained from previous tasks to enhance performance. It…
This article explores the future of deep learning and its impact on the field of artificial intelligence. It discusses the exponential growth in model…
Transfer learning is a game-changing technique in AI and machine learning that involves repurposing knowledge from one problem to solve another. It significantly accelerates…