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
Choi S, Bae J, Lee C, Kim Y, Kim J.
europepmc +4 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.
Ahmed MZI +3 more
europepmc +6 more sources
MEPFeatX-automated feature extraction of motor-evoked potentials in transcranial magnetic stimulation. [PDF]
Front NeurosciMotor 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.
Nguyen DTA +5 more
europepmc +4 more sources
A customized framework for regional classification of conifers using automated feature extraction. [PDF]
MethodsX, 2021 Pinyon and juniper expansion into sagebrush ecosystems is one of the major challenges facing land managers in the Great Basin. Effective pinyon and juniper treatment requires maps that accurately and precisely depict tree location and degree of woodland ...
Roth CL +6 more
europepmc +2 more sources
Mapathons versus automated feature extraction: a comparative analysis for strengthening immunization microplanning. [PDF]
Int J Health Geogr, 2021 Background Social instability and logistical factors like the displacement of vulnerable populations, the difficulty of accessing these populations, and the lack of geographic information for hard-to-reach areas continue to serve as barriers to global ...
Mendes A +9 more
europepmc +2 more sources
GinJinn: An object-detection pipeline for automated feature extraction from herbarium specimens. [PDF]
Appl Plant Sci, 2020 Premise The generation of morphological data in evolutionary, taxonomic, and ecological studies of plants using herbarium material has traditionally been a labor‐intensive task.
Ott T, Palm C, Vogt R, Oberprieler C.
europepmc +2 more sources
Automated feature extraction for planning state representation
Inteligencia ArtificialDeep learning methods have recently emerged as a mechanism for generating embeddings of planning states without the need to predefine feature spaces.
Oscar Sapena +2 more
doaj +3 more sources
OsteoNet-X: A deep residual learning framework for automated osteoporosis detection from knee X-ray images. [PDF]
PLoS OneOsteoporosis is a progressive skeletal disorder characterized by reduced bone mineral density and increased susceptibility to fractures, making early diagnosis essential for effective clinical intervention and long-term patient management.
Sangula SK, Ibrahim SPS.
europepmc +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 +4 more
doaj +1 more source
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 +7 more
doaj +1 more source