Results 21 to 30 of about 106,876 (300)

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, Jian Gu 0001, Matias Martinez, Thomas Durieux, Martin Monperrus   +4 more
openaire   +2 more sources

Deep Learning-Based Automated Lip-Reading: A Survey

IEEE Access, 2021
A survey on automated lip-reading approaches is presented in this paper with the main focus being on deep learning related methodologies which have proven to be more fruitful for both feature extraction and classification.
Souheil Fenghour, Daqing Chen, Kun Guo, Bo Li, Perry Xiao   +4 more
doaj   +1 more source

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, Jonas Schuff, Nathan Korda   +2 more
openaire   +2 more sources

A study on feature selection using multi-domain feature extraction for automated k-complex detection

Frontiers in Neuroscience, 2023
BackgroundK-complex detection plays a significant role in the field of sleep research. However, manual annotation for electroencephalography (EEG) recordings by visual inspection from experts is time-consuming and subjective.
Yabing Li, Yabing Li, Yabing Li, Xinglong Dong, Kun Song, Xiangyun Bai, Hongye Li, Fakhreddine Karray   +7 more
doaj   +1 more source

Multi-orientation local ternary pattern-based feature extraction for forensic dentistry

EURASIP Journal on Image and Video Processing, 2022
Accurate and automated identification of the deceased victims with dental radiographs plays a significant role in forensic dentistry. The image processing techniques such as segmentation and feature extraction play a crucial role in image retrieval in ...
Karunya Rajmohan, Askarunisa Abdul Khader   +1 more
doaj   +1 more source

Deep Learning-Based Feature Extraction of Acoustic Emission Signals for Monitoring Wear of Grinding Wheels

Sensors, 2022
Tool wear monitoring is a critical issue in advanced manufacturing systems. In the search for sensing devices that can provide information about the grinding process, Acoustic Emission (AE) appears to be a promising technology. The present paper presents
D. González, J. Alvarez, J. A. Sánchez, L. Godino, I. Pombo   +4 more
doaj   +1 more source

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
openaire   +1 more source

Attention-Guided Feature Extraction and Multiscale Feature Fusion 3D ResNet for Automated Pulmonary Nodule Detection

IEEE Access, 2022
Automatic detection of pulmonary nodules is critical for the early diagnosis and prevention of lung cancer. Computed tomography (CT) is an effective and economical lung cancer detection method. In CT images, the size and shape of pulmonary nodules appear
Guanglu Zhang, Hongjun Zhang, Yuhua Yao, Qiuhui Shen   +3 more
doaj   +1 more source

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, Stelios Papadopoulos, Zhuokun Ding, Paul G. Fahey, Eric Wang, Christos Papadopoulos, Alexander B. Kunin, Saumil Patel, J. Alexander Bae, Agnes L. Bodor, Derrick Brittain, JoAnn Buchanan, Daniel J. Bumbarger, Manuel A. Castro, Erick Cobos, Sven Dorkenwald, Leila Elabbady, Akhilesh Halageri, Zhen Jia, Chris Jordan, Dan Kapner, Nico Kemnitz, Sam Kinn, Kisuk Lee, Kai Li, Ran Lu, Thomas Macrina, Gayathri Mahalingam, Eric Mitchell, Shanka Subhra Mondal, Shang Mu, Barak Nehoran, Sergiy Popovych, Casey M. Schneider-Mizell, William Silversmith, Marc Takeno, Russel Torres, Nicholas L. Turner, William Wong, Jingpeng Wu, Szi-chieh Yu, Wenjing Yin, Daniel Xenes, Lindsey M. Kitchell, Patricia K. Rivlin, Victoria A. Rose, Caitlyn A. Bishop, Brock Wester, Emmanouil Froudarakis, Edgar Y. Walker, Fabian Sinz, H. Sebastian Seung, Forrest Collman, Nuno Maçarico da Costa, R. Clay Reid, Xaq Pitkow, Andreas S. Tolias, Jacob Reimer   +57 more
openaire   +4 more sources

Toward Automated Feature Extraction for Deep Learning Classification of Electrocardiogram Signals

IEEE Access, 2022
Many recent studies have focused on the automatic classification of electrocardiogram (ECG) signals using deep learning (DL) methods. Most rely on existing complex DL methods, such as transfer learning or providing the models with carefully designed ...
Fatima Sajid Butt, Matthias F. Wagner, Jorg Schafer, David Gomez Ullate   +3 more
doaj   +1 more source