Results 21 to 30 of about 59,683 (118)

Secformer: Privacy-preserving atomic-level componentized transformer-like model with MPC

Digital Communications and Networks
The global surge in Artificial Intelligence (AI) has been triggered by the impressive performance of deep-learning models based on the Transformer architecture.
Chi Zhang, Tao Shen, Fenhua Bai, Kai Zeng, Xiaohui Zhang, Bin Cao   +5 more
doaj   +1 more source

ArabBert-LSTM: improving Arabic sentiment analysis based on transformer model and Long Short-Term Memory

Frontiers in Artificial Intelligence
Sentiment analysis also referred to as opinion mining, plays a significant role in automating the identification of negative, positive, or neutral sentiments expressed in textual data.
Wael Alosaimi, Hager Saleh, Hager Saleh, Hager Saleh, Ali A. Hamzah, Nora El-Rashidy, Abdullah Alharb, Ahmed Elaraby, Sherif Mostafa   +8 more
doaj   +1 more source

Toward Early Detection of Depression: Detecting Depression Symptoms in Arabic Tweets Using Pretrained Transformers

IEEE Access
The COVID-19 pandemic and its associated setbacks have significantly impacted human mental health. Depression of various intensities has resulted due to a wide variety of losses that people have experienced.
Suzan Elmajali, Irfan Ahmad
doaj   +1 more source

Smart Defect Detection in Aero-Engines: Evaluating Transfer Learning with VGG19 and Data-Efficient Image Transformer Models

Machines
This study explores the impact of transfer learning on enhancing deep learning models for detecting defects in aero-engine components. We focused on metrics such as accuracy, precision, recall, and loss to compare the performance of models VGG19 and DeiT
Samira Mohammadi, Vahid Rahmanian, Sasan Sattarpanah Karganroudi, Mehdi Adda   +3 more
doaj   +1 more source

Automated Lithology Segmentation of 3D Point Clouds from Highwalls Using Deep Learning

Remote Sensing
Digital twins are increasingly being adopted to support efficient hazard assessment and predictive modelling. A key prerequisite for the development of reliable digital twins in rock slope engineering is the accurate identification and segmentation of ...
Umair Iqbal, Anna Giacomini, Klaus Thoeni   +2 more
doaj   +1 more source

Empowering Sentiment Analysis in African Low-Resource Languages Through Transformer Models and Strategic Language Selection

IEEE Access
This research addresses the significant challenges of sentiment analysis in low-resource African languages by utilizing advanced transformer-based models to bridge gaps in natural language processing (NLP) for underrepresented linguistic communities ...
Nilanjana Raychawdhary, Sutanu Bhattacharya, Cheryl Seals, Gerry V. Dozier   +3 more
doaj   +1 more source

WL-GraphTrax: A Graph-Transformer Framework for EEG-Based Cognitive Workload Classification

IEEE Access
Accurately measuring cognitive workload is critical in the development of adaptive human-machine systems, particularly in high-stakes environments such as driving.
Vishal Pandey, Nikhil Panwar, Partha Pratim Roy, Sushil Chandra   +3 more
doaj   +1 more source

BERT-OTA: Enhancing Hate Speech Detection With Ontology-Guided Transformer Attention

IEEE Access
The proliferation of hate speech on social media platforms presents a significant challenge for content moderation, requiring sophisticated detection methods that can understand both explicit and implicit forms of harmful content.
Mahmoud Abusaqer, Jamil Saquer, Mukulika Ghosh   +2 more
doaj   +1 more source

Learning the Grid: Transformer Architectures for Electricity Price Forecasting in the Australian National Market

Applied Sciences
The increasing adoption of highly variable renewable energy has introduced unprecedented volatility into the National Electricity Market (NEM), rendering traditional linear price forecasting models insufficient.
Mark Sinclair, Andrew J. Shepley, Farshid Hajati   +2 more
doaj   +1 more source

Transformer-Based Deep Learning for Multiplanar Cervical Spine MRI Interpretation: Comparison with Spine Surgeons and Radiologists

AI
Background: Degenerative cervical spondylosis (DCS) is a common and potentially debilitating condition, with surgery indicated in selected patients. Deep learning models (DLMs) can improve consistency in grading DCS neural stenosis on magnetic resonance ...
Aric Lee, Junran Wu, Changshuo Liu, Andrew Makmur, Yong Han Ting, You Jun Lee, Wilson Ong, Tricia Kuah, Juncheng Huang, Shuliang Ge, Alex Quok An Teo, Joey Chan Yiing Beh, Desmond Shi Wei Lim, Xi Zhen Low, Ee Chin Teo, Qai Ven Yap, Shuxun Lin, Jonathan Jiong Hao Tan, Naresh Kumar, Beng Chin Ooi, Swee Tian Quek, James Thomas Patrick Decourcy Hallinan   +21 more
doaj   +1 more source