Results 211 to 220 of about 40,989 (265)

Learning Moisture‐Induced Damage From Vision: Diffusion Models for Real‐Time Monitoring of Additive Manufacturing Processes

Advanced Science, EarlyView.
We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung, Yuna Yoo, Dharneedar Ravichandran, Dahyun Daniel Lim, Grace X. Gu   +4 more
wiley   +1 more source

Strategies for Class-Imbalanced Learning in Multi-Sensor Medical Imaging. [PDF]

Sensors (Basel)
Zhou D, Gao S, Huang X.
europepmc   +1 more source

Beyond Area Under the Receiver Operating Characteristic Curve: Evaluating Predictive Performance Metrics Under Class Imbalance in Real-World Clinical Data. [PDF]

JMIR Form Res
Ventura VDGJ, Andrade CMV, Almeida JM, Pessoa BP, Polanczyk CA, Nascimento GFD, Boersma E, Vianna HR, Farah KP, Rocha LCDD, Gonçalves MA, Marcolino MS.   +11 more
europepmc   +1 more source

A synthetic oversampling-based customized ResNet51-Conv1D framework for early colorectal cancer prediction using structured clinical data from the PLCO screening trial. [PDF]

BMC Med Inform Decis Mak
Prasath ST, Asha MM, Nagarajan B, Yesuraj R, Prathapchandran K, Sreeraman Y.   +5 more
europepmc   +1 more source

Data augmentation of event causality identification task with pre-trained language models. [PDF]

Sci Rep
Chun Y, Ha S, Bai J.
europepmc   +1 more source

Contextual deep learning for accurate news article categorisation with pre-trained embeddings. [PDF]

Sci Rep
Hamza A, Muhammad A, Abbas MS, Jan SU.
europepmc   +1 more source

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Assessing the data complexity of imbalanced datasets

Information Sciences, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Victor H. Barella, Luís Paulo F. Garcia, Marcilio C. P. de Souto, Ana Carolina Lorena, André C. P. L. F. de Carvalho   +4 more
openaire   +1 more source

Imbalanced Learning in Massive Phishing Datasets

2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), 2020
Phishing is one of the major threats facing internet users in today’s work. Such attacks continue costing billions of dollars to companies around the words thus requiring more efficient detection techniques to curb the danger. This paper proposes a big data friendly implementation of Multiclass Imbalance Learning in Ensembles through Selective Sampling
Ali Azari, Josephine M. Namayanja, Navneet Kaur, Vasundhara Misal, Suraksha Shukla   +4 more
openaire   +1 more source

Epileptic Seizure Prediction for Imbalanced Datasets

2019 Medical Technologies Congress (TIPTEKNO), 2019
In this study, the methods used in the classification of imbalanced data sets were applied to EEG signals obtained from epilepsy patients and epileptic seizures were estimated. Firstly, the data set was balanced by using under-sampling, oversampling, and synthetic minority over-sampling technique and classified with Support Vector Machines.
Coşgun, Ercan, Çelebi, A., Güllü, M. K.   +2 more
openaire   +2 more sources