AZoM

Why Deep Learning De-Noising is a Game Changer for X-Ray Technology

Innovative X-ray technology from Hamamatsu Photonics improves safety standards in food and non-destructive testing through ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
IEEE

IMed-CNN: Ensemble Learning Approach With Systematic Model Dropout for Enhanced Medical Image Classification Using Image Channels and Pixel Intervals

Abstract: To obtain light ensemble model through clearly explained effective ensemble member selection and finding data representation in various valuable forms are major challenges in medical image ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
Frontiers

GLN-LRF: global learning network based on large receptive fields for hyperspectral image classification

Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy. However, most current hyperspectral ...
IEEE

Medical Images Classification Using Hybrid Deep Learning CNN-PSO-GA

Abstract: Convolutional Neural Network (CNN) has made outstanding achievements in image processing and detection. The recent research uses CNN to classify the medical images, but this performance ...