Results 111 to 120 of about 27,643 (149)

Contrastive learning for nested Chinese Named Entity Recognition via template words

CAAI Transactions on Intelligence Technology, Volume 10, Issue 2, Page 450-459, April 2025.
Abstract Existing Chinese named entity recognition (NER) research utilises 1D lexicon‐based sequence labelling frameworks, which can only recognise flat entities. While lexicons serve as prior knowledge and enhance semantic information, they also pose completeness and resource requirements limitations.
Yuke Wang, Qiao Liu, Tingting Dai, Junjie Lang, Ling Lu, Yinong Chen   +5 more
wiley   +1 more source

Forecasting monthly runoff in a glacierized catchment: A comparison of extreme gradient boosting (XGBoost) and deep learning models. [PDF]

PLoS One
Hameed MM, Masood A, Hamid A, Elbeltagi A, Razali SFM, Salem A.   +5 more
europepmc   +1 more source

Appearance consistency and motion coherence learning for internal video inpainting

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internal learning‐based video inpainting methods have shown promising results by exploiting the intrinsic properties of the video to fill in the missing region without external dataset supervision. However, existing internal learning‐based video inpainting methods would produce inconsistent structures or blurry textures due to the insufficient
Ruixin Liu, Yuesheng Zhu, GuiBo Luo
wiley   +1 more source

Prediction of post-Schroth Cobb angle changes in adolescent idiopathic scoliosis patients based on neural networks and surface electromyography. [PDF]

Front Bioeng Biotechnol
Yin S, Chen J, Yan P.
europepmc   +1 more source

Enhancing patient rehabilitation predictions with a hybrid anomaly detection model: Density‐based clustering and interquartile range methods

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In recent years, there has been a concerted effort to improve anomaly detection techniques, particularly in the context of high‐dimensional, distributed clinical data. Analysing patient data within clinical settings reveals a pronounced focus on refining diagnostic accuracy, personalising treatment plans, and optimising resource allocation to ...
Murad Ali Khan, Jong‐Hyun Jang, Naeem Iqbal, Harun Jamil, Syed Shehryar Ali Naqvi, Salabat Khan, Jae‐Chul Kim, Do‐Hyeun Kim   +7 more
wiley   +1 more source

Improved Prediction of Hourly PM_2.5 Concentrations with a Long Short-Term Memory Optimized by Stacking Ensemble Learning and Ant Colony Optimization. [PDF]

Toxics
Liu Z, Hong X.
europepmc   +1 more source

Large Language Models With Contrastive Decoding Algorithm for Hallucination Mitigation in Low‐Resource Languages

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Neural machine translation (NMT) has advanced with deep learning and large‐scale multilingual models, yet translating low‐resource languages often lacks sufficient training data and leads to hallucinations. This often results in translated content that diverges significantly from the source text.
Zan Hongying, Arifa Javed, Muhammad Abdullah, Javed Rashid, Muhammad Faheem   +4 more
wiley   +1 more source

Forced Oscillation Detection via a Hybrid Network of a Spiking Recurrent Neural Network and LSTM. [PDF]

Sensors (Basel)
Yang X, Wang J, Huang X, Wang Y, Xiao X.
europepmc   +1 more source

Molecular Retrosynthesis Top‐K Prediction Based on the Latent Generation Process

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT In the field of organic synthesis, the core objective of retrosynthetic methods is to deduce possible synthetic routes and precursor molecules for complex target molecules. Traditional retrosynthetic methods, such as template‐based retrosynthesis, have high accuracy and interpretability in specific types of reactions but are limited by the ...
Yupeng Liu, Han Zhang, Rui Hu
wiley   +1 more source

Design of machine learning-based controllers for speed control of PMSM drive. [PDF]

Sci Rep
Tom AM, Daya JLF.
europepmc   +1 more source