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Found 13 papers, 2 papers with code
Comprehensive Validation on Reweighting Samples for Bias Mitigation via AIF360
Fairness AI aims to detect and alleviate bias across the entire AI development life cycle, encompassing data curation, modeling, evaluation, and deployment-a pivotal aspect of ethical AI implementation.
Medical Data Augmentation via ChatGPT: A Case Study on Medication Identification and Medication Event Classification
In the N2C2 2022 competitions, various tasks were presented to promote the identification of key factors in electronic health records (EHRs) using the Contextualized Medication Event Dataset (CMED).
Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image
However, prediction uncertainty of deep learning models for these tasks, which is very important to safety-critical applications like medical image processing, has not been comprehensively investigated.
Integrating Human-in-the-loop into Swarm Learning for Decentralized Fake News Detection
Moreover, it cannot fully involve user feedback in the loop of learning detection models for further enhancing fake news detection.
A Novel Dataset for Keypoint Detection of quadruped Animals from Images
In this paper, we studied the problem of localizing a generic set of keypoints across multiple quadruped or four-legged animal species from images.
Semi-supervised Learning for COVID-19 Image Classification via ResNet
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic in over 200 countries and territories, which has resulted in a great public health concern across the international community.
Efficient Privacy Preserving Edge Computing Framework for Image Classification
In order to extract knowledge from the large data collected by edge devices, traditional cloud based approach that requires data upload may not be feasible due to communication bandwidth limitation as well as privacy and security concerns of end users.
Cell Type Identification from Single-Cell Transcriptomic Data via Semi-supervised Learning
Then genes in these sentences are represented as gene embeddings to reduce data sparsity.
Ensemble Deep Learning on Time-Series Representation of Tweets for Rumor Detection in Social Media
By combining the proposed data pre-processing method with the ensemble model, better performance of rumor detection has been demonstrated in the experiments using PHEME dataset.
Two-path Deep Semi-supervised Learning for Timely Fake News Detection
In addition, we build a shared CNN to extract the low level features on both labeled data and unlabeled data to feed them into these two paths.
Deep Two-path Semi-supervised Learning for Fake News Detection
News in social media such as Twitter has been generated in high volume and speed.
Hierarchical Transfer Convolutional Neural Networks for Image Classification
In this paper, we address the issue of how to enhance the generalization performance of convolutional neural networks (CNN) in the early learning stage for image classification.
