[HTML][HTML] A new multi-label dataset for Web attacks CAPEC classification using machine learning techniques

TS Riera, JRB Higuera, JB Higuera, JJM Herraiz… - Computers & …, 2022 - Elsevier
Context There are many datasets for training and evaluating models to detect web attacks,
labeling each request as normal or attack. Web attack protection tools must provide …

Multi-label classification with label-specific feature generation: A wrapped approach

ZB Yu, ML Zhang - IEEE Transactions on Pattern Analysis and …, 2021 - ieeexplore.ieee.org
Label-specific features serve as an effective strategy to learn from multi-label data, where a
set of features encoding specific characteristics of each label are generated to help induce …

Multi-label modality enhanced attention based self-supervised deep cross-modal hashing

X Zou, S Wu, N Zhang, EM Bakker - Knowledge-Based Systems, 2022 - Elsevier
The recent deep cross-modal hashing (DCMH) has achieved superior performance in
effective and efficient cross-modal retrieval and thus has drawn increasing attention …

Online multi-label dependency topic models for text classification

S Burkhardt, S Kramer - Machine Learning, 2018 - Springer
Multi-label text classification is an increasingly important field as large amounts of text data
are available and extracting relevant information is important in many application contexts …

Bilabel-specific features for multi-label classification

ML Zhang, JP Fang, YB Wang - ACM Transactions on Knowledge …, 2021 - dl.acm.org
In multi-label classification, the task is to induce predictive models which can assign a set of
relevant labels for the unseen instance. The strategy of label-specific features has been …

Reconstruction regularized deep metric learning for multi-label image classification

C Li, C Liu, L Duan, P Gao… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
In this paper, we present a novel deep metric learning method to tackle the multi-label image
classification problem. In order to better learn the correlations among images features, as …

A cross-modal deep metric learning model for disease diagnosis based on chest x-ray images

Y Jin, H Lu, Z Li, Y Wang - Multimedia Tools and Applications, 2023 - Springer
The emergence of unknown diseases is often with few or no samples available. Zero-shot
learning and few-shot learning have promising applications in medical image analysis. In …

Compositional metric learning for multi-label classification

YP Sun, ML Zhang - Frontiers of Computer Science, 2021 - Springer
Multi-label classification aims to assign a set of proper labels for each instance, where
distance metric learning can help improve the generalization ability of instance-based multi …

[PDF][PDF] Learning label-specific multiple local metrics for multi-label classification

JX Mao, JY Hang, ML Zhang - Proceedings of the 33rd …, 2024 - palm.seu.edu.cn
Multi-label metric learning serve as an effective strategy to facilitate multi-label classification,
aiming to learn better similarity metrics from multilabel examples. Existing multi-label metric …

Multi-label-based similarity learning for vehicle re-identification

S Alfasly, Y Hu, H Li, T Liang, X Jin, B Liu… - IEEE Access, 2019 - ieeexplore.ieee.org
The massive attention to the surveillance video-based analysis makes the vehicle re-
identification one of the current hot areas of interest to study. Extracting discriminative visual …