IEEE

A Disjoint Samples-Based 3D-CNN With Active Transfer Learning for Hyperspectral Image Classification

Abstract: Convolutional neural networks (CNNs) have been extensively studied for hyperspectral image classification (HSIC). However, CNNs are critically attributed to a large number of labeled ...
C&EN

Coal Classification Based on Reflection Spectroscopy and the IAT-TELM Algorithm

School of Information Science and Engineering, Northeastern University, Shenyang 110819, China Liaoning Key Laboratory of Intelligent Diagnosis and Safety for Metallurgical Industry, Northeastern ...
Scientific Research Publishing

Deep Learning-Based Multi-Class Classification of Retinal Diseases from OCT Images Using Transfer Learning ()

1 Amazon Web Services, Seattle, USA. 2 Rajiv Gandhi University of Knowledge Technologies, Nuzvid, India. Optical Coherence Tomography (OCT) is a non-invasive imaging modality widely employed for ...
IEEE

Implementation and Performance Evaluation of Improved Hybrid Deep Learning Approach for Anomaly Detection and Classification in Lung CT Images

Abstract: The goal of this study is to create and test improved enhanced deep learning approaches for anomaly detection and classification in CT images, specifically lung cancer images. The Improved ...
The Lancet

Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study

fDepartment of Nephrology and Immunology, RWTH Aachen University Hospital, Aachen, Germany gDepartment of Medicine III, RWTH Aachen University Hospital, Aachen, Germany hDepartment of Pathology, ...
PNAS

Temperature dependence of parasitoid infection and abundance of a diatom revealed by automated imaging and classification

Diatoms are unicellular algae whose “blooms” are associated with high primary productivity, prolific fisheries, and carbon flux to the deep ocean. Despite its potential impact on marine food webs, ...
Frontiers

A CNN-Based Deep Learning Approach for SSVEP Detection Targeting Binaural Ear-EEG

This paper discusses a machine learning approach for detecting SSVEP at both ears with minimal channels. SSVEP is a robust EEG signal suitable for many BCI applications. It is strong at the visual ...
GitHub

Explainable AI: interpreting the classification performed by deep learning with LIME

This demo shows how to interpret the classification by CNN using LIME (Local Interpretable Model-agnostic Explanations) [1]. This demo was created based on [1], but the implementation might be a ...