Technology Networks

Deep Learning for Variant Calling: How DeepVariant and Neural Networks Are Improving Genomic Accuracy

Deep learning variant calling has transformed genomic accuracy. Discover how DeepVariant works, outperforms classical tools, ...
Technology Networks

Cellpose, StarDist, and the Deep Learning Cell Segmentation Revolution

Compare deep learning cell segmentation tools Cellpose and StarDist: how each works, how they differ by imaging type, and ...

Deep learning reveals nanoparticle shape from routine tracking analysis without new hardware

Researchers at the University of Tokyo and the Innovation Center of NanoMedicine (iCONM) have developed an artificial ...
Frontiers

Artificial Intelligence and Multimodal Imaging of the Temporomandibular Joint: From Morphology to Clinical Decision Support

The field of orofacial medicine increasingly recognizes the temporomandibular joint (TMJ) as a complex anatomical and functional unit whose disorders can ...
Tech Xplore

Reliably detecting and clearly explaining deepfake images

Artificial intelligence can now generate images that are virtually indistinguishable from real ones. Researchers at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation ...
News-Medical.Net

Advancing 3D imaging, automation, and phenotypic discovery with AI-driven high-content screening

In this interview, AZoLife Sciences speaks with Boyd Butler, a microscopy and high-content screening expert at Molecular ...
The Manila Times

WiMi Develops Quantum Convolutional Neural Network Model for Classical Data Classification

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ('WIMI' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, has completed systematic benchmark testing on fully ...
IEEE

Hyperspectral Image Classification With Deep Learning Models

Abstract: Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem ...
IEEE

Deep Learning Ensemble for Hyperspectral Image Classification

Abstract: Deep learning models, especially deep convolutional neural networks (CNNs), have been intensively investigated for hyperspectral image (HSI) classification due to their powerful feature ...
ascopubs.org

Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance

Using whole-slide hematoxylin and eosin images from 214 patients with glioblastoma in The Cancer Genome Atlas (TCGA), a fine-tuned convolutional neural network model extracted deep learning features.