A comprehensive survey on applications of transformers for deep learning tasks
Abstract Transformers are Deep Neural Networks (DNN) that utilize a self-attention
mechanism to capture contextual relationships within sequential data. Unlike traditional …
mechanism to capture contextual relationships within sequential data. Unlike traditional …
[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning
Class imbalance occurs when the class distribution is not equal. Namely, one class is under-
represented (minority class), and the other class has significantly more samples in the data …
represented (minority class), and the other class has significantly more samples in the data …
Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation
As acquiring pixel-wise annotations of real-world images for semantic segmentation is a
costly process, a model can instead be trained with more accessible synthetic data and …
costly process, a model can instead be trained with more accessible synthetic data and …
[HTML][HTML] Financial fraud: a review of anomaly detection techniques and recent advances
With the rise of technology and the continued economic growth evident in modern society,
acts of fraud have become much more prevalent in the financial industry, costing institutions …
acts of fraud have become much more prevalent in the financial industry, costing institutions …
Map** the NFT revolution: market trends, trade networks, and visual features
Abstract Non Fungible Tokens (NFTs) are digital assets that represent objects like art,
collectible, and in-game items. They are traded online, often with cryptocurrency, and are …
collectible, and in-game items. They are traded online, often with cryptocurrency, and are …
Towards personalized federated learning
In parallel with the rapid adoption of artificial intelligence (AI) empowered by advances in AI
research, there has been growing awareness and concerns of data privacy. Recent …
research, there has been growing awareness and concerns of data privacy. Recent …
[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
threatening. Network intrusion detection has been widely accepted as an effective method to …
Using machine learning approaches for multi-omics data analysis: A review
With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …
become essential for biomedical studies to undertake an integrative (combined) approach to …
AI applications to medical images: From machine learning to deep learning
Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …
research and healthcare services. This review focuses on challenges points to be clarified …