Neural networks and label-free microscopy enable accurate detection of pancreatic tumors

Pancreatic neuroendocrine neoplasms (PNENs) are a rare form of cancer that affects hormone-producing cells in the pancreas.
EurekAlert!

Label-free multiphoton microscopy and deep learning can be used in combination to classify pancreatic neuroendocrine neoplasms with high accuracy—a significant step toward ...

Label-free multiphoton microscopy and deep learning can be used in combination to classify pancreatic neuroendocrine neoplasms with high accuracy—a significant step toward automated digital pathology ...
EurekAlert!

High-accuracy tumor detection with label-free microscopy and neural networks

University of Arizona researchers have demonstrated that multiphoton microscopy (MPM), combined with machine learning and deep learning techniques, can accurately distinguish pancreatic neuroendocrine ...
GitHub

multiclass-image-classification

Trained a deep learning-based system using high-resolution Sentinel-2 imagery and CNNs to classify land into water, vegetation, urban and barren areas with 92.4% validation accuracy.
IEEE

Image Classification Model for Data Sentry of Plant Diseases Using Convolutional Neural Networks

Abstract: This study examines the effectiveness of using machine learning-based image recognition model for classifying common diseases in crops. This study addresses the critical need for swift and ...
IEEE

Hyperspectral Image Classification Using Gated Adaptable Convolutional-Based Kolmogorov–Arnold Network

Abstract: Vision transformers (ViTs) and convolutional neural networks (CNNs) have demonstrated remarkable performance in classifying complicated hyperspectral images (HSIs). However, these models ...
C&EN

GSH and Halides Directed Controllable Synthesis of Chiral Gold Nanostars for Sensitive Diagnosis of Nephritis Types Using SERS and Transformer Neural Network

Institute of Digitized Medicine and Intelligent Technology, Wenzhou Medical University, Wenzhou 325000, P. R. China ...