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 ...
IEEE

Nanobot-Assisted Pollination for Sustainable Agriculture: A Review of Image Classification and Deep Learning Techniques With YOLO, SLAM, and MATLAB

Abstract: The global decrease in native pollinators poses a substantial challenge to agricultural production and food security, particularly in malnutrition prone countries. There is a huge potential ...
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 ...
Nature

Deep learning-driven brain tumor classification and segmentation using non-contrast MRI

Magnetic Resonance Imaging (MRI) remains a cornerstone in the diagnosis and management of brain tumors due to its superior soft tissue contrast and non-invasive nature. However, traditional diagnostic ...
EDN

Applying AI to RF design

Human inventions, namely engineered systems, have relied on fundamental discoveries in physics and mathematics, e.g., Maxwell’s equations, Quantum mechanics, Information theory, etc., thereby applying ...
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

Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment

The phenotypic age of the human brain, as revealed via deep learning of anatomic magnetic resonance images, reflects patterns of structural change related to cognitive decline. Our interpretable deep ...
Frontiers

3D Inundation Mapping: A Comparison Between Deep Learning Image Classification and Geomorphic Flood Index Approaches

Inundation mapping is a critical task for damage assessment, emergency management, and prioritizing relief efforts during a flooding event. Remote sensing has been an effective tool for interpreting ...
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 ...
Scientific Research Publishing

Food Ingredients Identification from Dish Images by Deep Learning ()

Diet plays an important role in people’s daily life with its strong correlation to health and chronic diseases. Meanwhile, deep based food computing emerges to provide lots of works which including ...