Results 1 to 10 of about 101,355 (253)
Attention-Based Automated Feature Extraction for Malware Analysis. [PDF]
Sensors (Basel), 2020 Every day, hundreds of thousands of malicious files are created to exploit zero-day vulnerabilities. Existing pattern-based antivirus solutions face difficulties in coping with such a large number of new malicious files. To solve this problem, artificial intelligence (AI)-based malicious file detection methods have been proposed.
Choi S, Bae J, Lee C, Kim Y, Kim J.
europepmc +5 more sources
Automated Feature Extraction on AsMap for Emotion Classification Using EEG. [PDF]
Sensors (Basel), 2022 Emotion recognition using EEG has been widely studied to address the challenges associated with affective computing. Using manual feature extraction methods on EEG signals results in sub-optimal performance by the learning models. With the advancements in deep learning as a tool for automated feature engineering, in this work, a hybrid of manual and ...
Ahmed MZI +3 more
europepmc +6 more sources
MEPFeatX—automated feature extraction of motor-evoked potentials in transcranial magnetic stimulation [PDF]
Frontiers in NeuroscienceMotor evoked potentials (MEPs) are an important measure in transcranial magnetic stimulation (TMS) when assessing neuronal excitability in clinical diagnostics related to motor function, as well as in neuroscience research.
Elisa Kallioniemi +2 more
exaly +4 more sources
Automated Classification of Overfitting Patches With Statically Extracted Code Features [PDF]
IEEE Transactions on Software Engineering, 2022 Automatic program repair (APR) aims to reduce the cost of manually fixing software defects. However, APR suffers from generating a multitude of overfitting patches, those patches that fail to correctly repair the defect beyond making the tests pass. This paper presents a novel overfitting patch detection system called ODS to assess the correctness of ...
He Ye +4 more
openaire +2 more sources
The Automated Bias Triangle Feature Extraction Framework
CoRR, 2023 Bias triangles represent features in stability diagrams of Quantum Dot (QD) devices, whose occurrence and property analysis are crucial indicators for spin physics. Nevertheless, challenges associated with quality and availability of data as well as the subtlety of physical phenomena of interest have hindered an automatic and bespoke analysis framework,
Madeleine Kotzagiannidis +2 more
openaire +2 more sources
Automated Extraction of Secondary Flow Features [PDF]
43rd AIAA Aerospace Sciences Meeting and Exhibit, 2005 The use of Computational Fluid Dynamics (CFD) has become standard practice in the design and development of the major components used for air and space propulsion. To aid in the post-processing and analysis phase of CFD many researchers now use automated feature extraction utilities.
Suzanne Dorney, Robert Haimes
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NEURD offers automated proofreading and feature extraction for connectomics
Nature, 2023 We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et ...
Brendan Celii +57 more
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Algorithm for Automated Segmentation and Feature Extraction of Thermal Images
, 2020 Medical infrared thermal imaging techniques can provide the high-quality images for monitoring and pre-clinical diagnostic of the diseases by showing the thermal abnormalities available in the body. Its biggest advantage is non-contact, non-invasive and very fast way of use.
Poplavska, Anna +4 more
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A Scalable Automated Diagnostic Feature Extraction System for EEGs
2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), 2019 Researchers using Electroencephalograms ("EEGs") to diagnose clinical outcomes often run into computational complexity problems. In particular, extracting complex, sometimes nonlinear, features from a large number of time-series often require large amounts of processing time.
Prakhar Agrawal +9 more
openaire +3 more sources
Automated SAT Problem Feature Extraction using Convolutional Autoencoders
2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), 2021 The Boolean Satisfiability Problem (SAT) was the first known NP-complete problem and has a very broad literature focusing on it. It has been applied successfully to various real-world problems, such as scheduling, planning and cryptography. SAT problem feature extraction plays an essential role in this field. SAT solvers are complex, fine-tuned systems
Marco Dalla +2 more
openaire +3 more sources