Led by Professor Fu Jin, the study addresses a critical challenge in radiation therapy: balancing the computational speed and ...

Abstract: Imbalanced image classification faces critical challenges in balancing the quality and diversity of synthetic minority samples. This article proposes the improved estimation distribution ...

UMass Lowell business students tour the gymnasium at the Boys and Girls Club of Greater Lowell. UMass Lowell has received a renewed Carnegie Community Engagement Classification reflecting a ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Researchers from King Abdullah University of Science and Technology (KAUST) have developed deepBlastoid, the first deep-learning platform ...

Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current ...

You will be redirected to our submission process. Cervical cancer detection and diagnosis are undergoing a transformation with the integration of advanced deep learning (DL) technologies. Despite ...

Abstract: Deep learning has emerged as a critical paradigm in hyperspectral image (HSI) classification, addressing the inherent challenges posed by high-dimensional data and limited labeled samples.

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 ...