Medical Device and Diagnostic Industry (MD+DI)

The AI Era: How Deep Learning is Overcoming Data Scarcity in Medical Imaging

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

Light-programmed system projects 28-layer 3D images in single shot

Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan ...
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 ...
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 ...
Nature

A lightweight deep learning model for multi-plant biotic stress classification and detection for sustainable agriculture

Plant pathogens and pests hinder general plant health, resulting in poor agricultural yields and production. These threaten global food security and cause environmental and economic shortages. Amidst ...
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 ...
LinkedIn

#18 Quick Analysis on AI Report on ImageNet Classification with Deep Convolutional Neural Networks by Geoffrey Hinton

This is a research paper titled "ImageNet Classification with Deep Convolutional Neural Networks" authored by Geoffrey Hinton, Alex Krizhevsky, and Ilya Sutskever. This paper is a seminal work in the ...
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 ...