Abstract: Aiming at the challenges of high intra-class disparity and low inter-class disparity in fine-grained image classification, a multi-branch fine-grained image classification method based on ...
BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...
Abstract: As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural ...
Beans are a legume that is widely grown and consumed globally, being the staple food for humans in developing countries. Nitrogen (N) is the most limiting nutrient for yield and foliar analysis is ...
This repository contains the full codebase developed at Helmholtz Munich for the CytoDiff project. The goal is to improve white blood cell image classification by augmenting real-world datasets with ...
ABSTRACT: Accurate histological classification of lung cancer in CT images is essential for diagnosis and treatment planning. In this study, we propose a vision transformer (ViT) model with two-stage ...
Following last year’s announcement, Google Messages is rolling out Sensitive Content Warnings that blur nude images on Android. This image classification, which does not currently apply to videos, ...
Introduction: A novel classification scheme for endplate lesions, based on T2-weighted images from magnetic resonance imaging (MRI) scan, has been recently introduced and validated. The scheme ...
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