IEEE

Prompt-Based Label-Aware Framework for Few-Shot Multi-Label Text Classification

Abstract: Prompt-based learning has demonstrated remarkable success in few-shot text classification, outperforming the traditional fine-tuning approach. This method transforms a text input into a ...
Electric Bike Explorer on MSN

Mississippi e-bike laws (2026 guide): Everything you need to know

If you’re planning to ride an electric bike in Mississippi, it’s important to understand the state’s e-bike laws before you ...
IEEE

Multi-Instance Multi-Label Learning for Multi-Class Classification of Whole Slide Breast Histopathology Images

Abstract: Digital pathology has entered a new era with the availability of whole slide scanners that create the high-resolution images of full biopsy slides. Consequently, the uncertainty regarding ...
GitHub

NeuralClassifier: An Open-source Neural Hierarchical Multi-label Text Classification Toolkit

NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios. A salient feature ...
InfoWorld

Using AI-powered email classification to accelerate help desk responses

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...
LinkedIn

Multiclass vs. Multilabel Classification: Understanding the Differences Clearly

In machine learning, correctly categorizing data is fundamental to solving real-world problems. However, the task of classification isn't always straightforward. While basic binary classification ...
Visual Studio Magazine

Implementing k-NN Classification Using C#

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...
Scientific Research Publishing

Image Classification Based on Vision Transformer ()

This research introduces an innovative approach to image classification, by making use of Vision Transformer (ViT) architecture. In fact, Vision Transformers (ViT) have emerged as a promising option ...
Frontiers

Multi-label classification of retinal disease via a novel vision transformer model

The precise identification of retinal disorders is of utmost importance in the prevention of both temporary and permanent visual impairment. Prior research has yielded encouraging results in the ...
Frontiers

Multi-view image-based behavior classification of wet-dog shake in Kainate rat model

The wet-dog shake behavior (WDS) is a short-duration behavior relevant to the study of various animal disease models, including acute seizures, morphine abstinence, and nicotine withdrawal. However, ...
Visual Studio Magazine

Multi-Class Classification Using a scikit Decision Tree

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...