IEEE

Hierarchy-Aware and Knowledge-Guided Learning for Multi-Label Classification of Retinal Diseases From Fundus Images

Abstract: Retinal diseases (RD) are major causes of global vision impairment. Automated diagnosis using fundus images has significant clinical value, particularly in multi-label classification of RD.
GitHub

Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A Large-scale Dataset and Dual-stream ...

This repository is the code implementation of the paper Fine-grained Hierarchical Crop Type Classification from Integrated Hyperspectral EnMAP Data and Multispectral Sentinel-2 Time Series: A ...
Healio

Five-grade imaging classification system may reduce primary periphyseal stress injury

A five-grade imaging classification system and diagnostic therapeutic algorithm may reduce the risk for primary periphyseal ...
The Tech Edvocate

“The Difference Between Bloom’s Original and Revised Taxonomy: What Changed and Why It Matters”

Spread the love“`html In the realm of education, few frameworks have shaped pedagogical practices as profoundly as Bloom’s Taxonomy. Originally developed in 1956 by a team of cognitive psychologists ...

MicroCloud Hologram Inc. Develops Approximate Quantum State Preparation and Entanglement-Dependent Complexity Algorithm Technology

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, has announced a groundbreaking achievement of great theoretical and engineering significance: its ...
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

CPGNet: Multimodal Graph Learning with Hierarchical Category Guidance for Multi-Label Whole Slide Image Classification

Abstract: The analysis of WSI categories in digital pathology is critical for clinician decision making regarding the diagnosis, treatment, and prognosis of cancer patients. However, current automated ...