Nature

Crop-weed classification using deep learning: a comparative study of CNNs, vision transformers, and interpretable models

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...
Frontiers

Integrating Species Distribution Models, GeoAI, and Citizen Science: Predictive Tools for Bird Habitat Assessment and Conservation Decision-Making

BackgroundBird populations are facing unprecedented global pressures from climate change, habitat fragmentation, land use ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
The American Journal of Managed Care

Smartphone-Enabled Imaging Part of Strategy in Screening Rare Ocular Malignancies

A three-stage pipeline progressed from slit-lamp image training to smartphone optimization and public self-capture, incorporating human-computer interface refinements and preprocessing to improve real ...
IEEE

Model Agnostic Contrastive Explanations for Classification Models

Abstract: Extensive surveys on explanations that are suitable for humans, claims that an explanation being contrastive is one of its most important traits. A few methods have been proposed to generate ...
IEEE

A Survey on Confidence Calibration of Deep Learning-Based Classification Models Under Class Imbalance Data

Abstract: Confidence calibration in classification models is a vital technique for accurately estimating the posterior probabilities of predicted results, which is crucial for assessing the likelihood ...