Results 21 to 30 of about 957,081 (355)

Automated recognition of ruffed grouse drumming in field recordings

Wildlife Society Bulletin, 2023
Ruffed grouse (Bonasa umbellus) populations are declining throughout their range, which has prompted efforts to understand drivers of the decline. Ruffed grouse monitoring efforts often rely on acoustic drumming surveys, in which a surveyor listens for ...
Samuel Lapp, Jeffery L. Larkin, Halie A. Parker, Jeffery T. Larkin, Dakotah R. Shaffer, Carolyn Tett, Darin J. McNeil, Cameron J. Fiss, Justin Kitzes   +8 more
doaj   +1 more source

Pattern Recognition in Multivariate Time Series: Towards an Automated Event Detection Method for Smart Manufacturing Systems

Journal of Manufacturing and Materials Processing, 2020
This paper presents a framework to utilize multivariate time series data to automatically identify reoccurring events, e.g., resembling failure patterns in real-world manufacturing data by combining selected data mining techniques.
Vadim Kapp, M. May, G. Lanza, Thorsten Wuest   +3 more
semanticscholar   +1 more source

Review of Printed Fabric Pattern Segmentation Analysis and Application

AUTEX Research Journal, 2020
Image processing of digital images is one of the essential categories of image transformation in the theory and practice of digital pattern analysis and computer vision.
Kumah Charles, Raji Rafiu King, Pan Ruru
doaj   +1 more source

LEDPatNet19: Automated Emotion Recognition Model based on Nonlinear LED Pattern Feature Extraction Function using EEG Signals

Cognitive Neurodynamics, 2021
Electroencephalography (EEG) signals collected from human brains have generally been used to diagnose diseases. Moreover, EEG signals can be used in several areas such as emotion recognition, driving fatigue detection.
T. Tuncer, S. Dogan, A. Subasi
semanticscholar   +1 more source

KurdFace Morph Dataset Creation Using OpenCV

Science Journal of University of Zakho, 2022
Automated facial recognition is rapidly being used to reliably identify the identities of individuals for a variety of applications, from automated border control to unlocking mobile phones.
Arezu Rezgar Hussein, Rasber Dhahir Rashid   +1 more
doaj   +1 more source

Pattern recognition methodologies for pollen grain image classification: a survey

Machine Vision and Applications, 2022
In a large number of scientific areas, such as immunology, forensics, paleoecology, and archeology, the study of pollen, i.e., palynology, plays an important role: from tracking climate changes, studying allergies, to forensic investigations or honey ...
Philipp Viertel, Matthias König
semanticscholar   +1 more source

Accurate species identification of food-contaminating beetles with quality-improved elytral images and deep learning

Frontiers in Artificial Intelligence, 2022
Food samples are routinely screened for food-contaminating beetles (i.e., pantry beetles) due to their adverse impact on the economy, environment, public health and safety.
Halil Bisgin, Tanmay Bera, Leihong Wu, Hongjian Ding, Neslihan Bisgin, Zhichao Liu, Monica Pava-Ripoll, Amy Barnes, James F. Campbell, Himansi Vyas, Cesare Furlanello, Weida Tong, Joshua Xu   +12 more
doaj   +1 more source

Evaluation of acoustic pattern recognition of nightingale (Luscinia megarhynchos) recordings by citizens [PDF]

Research Ideas and Outcomes, 2020
Acoustic pattern recognition methods introduce new perspectives for species identification, biodiversity monitoring and data validation in citizen science but are rarely evaluated in real world scenarios. In this case study we analysed the performance of
Marcel Stehle, Mario Lasseck, Omid Khorramshahi, Ulrike Sturm   +3 more
doaj   +3 more sources

Pattern recognition software and techniques for biological image analysis.

PLoS Computational Biology, 2010
The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse ...
Lior Shamir, John D Delaney, Nikita Orlov, D Mark Eckley, Ilya G Goldberg   +4 more
doaj   +1 more source

Magnetic Flux Leakage Sensing and Artificial Neural Network Pattern Recognition-Based Automated Damage Detection and Quantification for Wire Rope Non-Destructive Evaluation

Italian National Conference on Sensors, 2018
In this study, a magnetic flux leakage (MFL) method, known to be a suitable non-destructive evaluation (NDE) method for continuum ferromagnetic structures, was used to detect local damage when inspecting steel wire ropes.
Ju-Won Kim, S. Park
semanticscholar   +1 more source