Results 31 to 40 of about 59,683 (118)

LegNER: a domain-adapted transformer for legal named entity recognition and text anonymization

Frontiers in Artificial Intelligence
The increasing demand for scalable and privacy-preserving processing of legal documents has intensified the need for accurate Named Entity Recognition (NER) systems tailored to the legal domain.
Ioannis Karamitsos, Nikolaos Roufas, Khalil Al-Hussaeni, Andreas Kanavos   +3 more
doaj   +1 more source

Breast Cancer Classification Using Fine-Tuned SWIN Transformer Model on Mammographic Images

Analytics
Breast cancer is the most prevalent type of disease among women. It has become one of the foremost causes of death among women globally. Early detection plays a significant role in administering personalized treatment and improving patient outcomes ...
Oluwatosin Tanimola, Olamilekan Shobayo, Olusogo Popoola, Obinna Okoyeigbo   +3 more
doaj   +1 more source

Integrating AI for In-Depth Segmentation of Coastal Environments in Remote Sensing Imagery

Remote Sensing
Mapping coastal landforms is critical for the sustainable management of ecosystems influenced by both natural dynamics and human activity. This study investigates the application of Transformer-based semantic segmentation models for pixel-level ...
Pelagia Drakopoulou, Paraskevi Tzouveli, Aikaterini Karditsa, Serafim Poulos   +3 more
doaj   +1 more source

Enhanced Multi-Task Traffic Forecasting in Beyond 5G Networks: Leveraging Transformer Technology and Multi-Source Data Fusion

Future Internet
Managing cellular networks in the Beyond 5G (B5G) era is a complex and challenging task requiring advanced deep learning approaches. Traditional models focusing on internet traffic (INT) analysis often fail to capture the rich temporal and spatial ...
Ibrahim Althamary, Rubbens Boisguene, Chih-Wei Huang   +2 more
doaj   +1 more source

Deconstructing a Minimalist Transformer Architecture for Univariate Time Series Forecasting

Algorithms
This paper provides a detailed breakdown of a minimalist, fundamental Transformer-based architecture for forecasting univariate time series. It describes each processing step in detail, from input embedding and positional encoding to self-attention ...
Filippo Garagnani, Vittorio Maniezzo
doaj   +1 more source

Beyond Cross-Entropy: Discounted Least Information Theory of Entropy (DLITE) Loss and the Impact of Loss Functions on AI-Driven Named Entity Recognition

Information
Loss functions play a significant role in shaping model behavior in machine learning, yet their design implications remain underexplored in natural language processing tasks such as Named Entity Recognition (NER).
Sonia Pascua, Michael Pan, Weimao Ke
doaj   +1 more source

Localized Query Attack Toward Transformer-Based Visible Object Detectors

Sensors
Transformer-based detectors have demonstrated exceptional accuracy in visible-object detection tasks. However, adversarial patches, specific types of adversarial examples, can disrupt these detectors by introducing unrestricted perturbations into ...
Yang Wang, Ang Li, Zhen Yang, Xunyun Liu
doaj   +1 more source

Optimizing Air Pollution Forecasting Models Through Knowledge Distillation: A Novel GCN and TRANS_GRU Methodology for Indian Cities

IEEE Access
As air pollution remains a pressing issue affecting environmental and public health, precise forecasting and monitoring are essential. Machine learning and deep learning models are increasingly applied in air pollution studies, using their advanced ...
Sudhir Kumar, Vaneet Kour, Ankit Raj, Tagru Tapung, Shivendu Mishra, Rajiv Misra, T. N. Singh   +6 more
doaj   +1 more source

SQ-LoRA: Memory-Efficient Language Model Compression Through Stable-Rank-Guided Quantization for Edge Computing Applications

Applied Sciences
The deployment of transformer-based language models on resource-constrained edge devices presents fundamental challenges in computational efficiency and memory utilization. We introduce SQ-LoRA (Stable-rank Quantized Low-Rank Adaptation), a theoretically
Seda Bayat Toksöz, Gültekin Işik
doaj   +1 more source

Hotel Rating Prediction from Online Guest Feedback Using Reliability Modeling and Neural Text Analysis

Computers
Online hotel reviews provide a major source of information for understanding guest satisfaction, yet rating prediction remains difficult because review text is often short, highly skewed toward positive scores, and affected by inconsistent or repetitive ...
Milena Nikolić, Miloš Stojanović, Marina Marjanović   +2 more
doaj   +1 more source