Deep learning is a rapidly evolving subset of AI that is driving technological advancements and shaping the future of machine perception and analysis. This…
Browsing: Transfer Learning
This article presents ECOLE, a deep learning-based method for somatic and germline CNV calling on WES data. ECOLE is based on a variant of…
This article discusses recent advancements in agricultural computer vision, which have heavily relied on deep learning models. The article highlights the inadequacy of existing…
Machine learning anti-patterns are common mistakes made in the development or application of ML models that can lead to poor performance, biases, overfitting, or…
This study explores the use of machine learning approaches for the automatic detection of Parkinson’s disease using voice recordings. The study collected samples from…
This article presents a review of various deep and machine learning techniques used to identify various complications in diabetic retinopathy (DR). The authors propose…
Deep learning is revolutionizing many industries, with trends such as Explainable AI, Self-Supervised Learning, Transfer Learning, Edge Computing, and Quantum Computing driving its future.…
Deep learning is a subset of machine learning that has made significant strides in recent years, reshaping industries and opening up new possibilities. This…
Transfer learning is a process in which a model is learnt in one setting and is then used to improve generalization in another setting.…
This Special Issue is dedicated to exploring the potential of deep transfer learning in remote sensing (RS) image processing. Transfer learning attempts to reduce…