Damage Detection in Plates with the Use of Laser-Measured Mode Shapes by Ziemowit Dworakowski, Kajetan Dziedziech, Pawel Zdziebko, Krzysztof Mendrok

“…The conclusions of the laboratory experiment confirm the damage detection capabilities of the methods but question their damage localization potential.…”
Get full text

STED nanoscopy with time-gated detection: theoretical and experimental aspects. by Giuseppe Vicidomini, Andreas Schönle, Haisen Ta, Kyu Young Han, Gael Moneron, Christian Eggeling, Stefan W Hell

“…Gated CW-STED nanoscopy is in essence limited (only) by the reduction of the signal that is associated with gating. Time-gated detection also reduces/suppresses the influence of local variations of the fluorescence lifetime on STED microscopy resolution.…”
Get full text

Towards Accurate Pupil Detection Based on Morphology and Hough Transform by AlShemmary et al.

“…This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. …”
Get full text

SEOPREVALENCE AND MOLECULAR DETECTION OF BABESIA SPECIES IN CATTLE IN BAGHDAD CITY by Abdelrasol .KH.Saeed, Mohammed.TH.Salih, Mohammed Sh. Jebur

“…During June -December 2016, for detection of cattle Babesiosis. One hundred fifty (150) clinically healthy local cattle breeds of different ages, and from both sex were examined by routine blood smear examination, molecular detection of Babesiosis by Conventional polymerase chain reaction PCR and by ELISA test. …”
Get full text

Detecting the Boundary of Sensor Networks from Limited Cyclic Information by Carlos Lara-Alvarez, Juan J. Flores, Chieh-Chih Wang

“…Our proposed approach uses local information to recognize points on the boundary. …”
Get full text

Study on the Lightweighting Strategy of Target Detection Model with Deep Learning by Junli Hu

“…Aiming at the high miss detection and false detection rate of traditional SSD (single shot multibox detector) target detection algorithm in target detection, this paper proposes a lightweight detection algorithm for deep learning target detection model in order to improve the detection accuracy. …”
Get full text

Broadcasting American red squirrel vocalizations influences detection probability. by Ian G Warkentin, Heather E Spicer, Jenna P B McDermott, Darroch M Whitaker, Erin E Fraser

“…Response to vocalization broadcast was highest when local population density was lowest. Higher detection probability during the initial silent periods of our surveys, when population density was high, likely reflects the greater chance of spontaneous vocalizations in response to the behavior of neighbors.…”
Get full text

A Lightweight Approach to Comprehensive Fabric Anomaly Detection Modeling by Shuqin Cui, Weihong Liu, Min Li

“…In order to solve the problem of high computational resource consumption in fabric anomaly detection, we propose a lightweight network, GH-YOLOx, which integrates ghost convolutions and hierarchical GHNetV2 backbone together to capture both local and global anomaly features. …”
Get full text

A Comprehensive Investigation of Fraud Detection Behavior in Federated Learning by Sun Rui

“…This research delves into the application of Federated Learning (FL) models for detecting fraud across different financial bodies. …”
Get full text

An anomaly detection scheme for data stream in cold chain logistics. by Zhibo Xie, Heng Long, Chengyi Ling, Yingjun Zhou, Yan Luo

“…Anomaly detection is widely used in cold chain logistics (CCL). …”
Get full text

Near-Field Microwave Sensing for Chip-Level Tamper Detection by Maryam Saadat Safa, Shahin Tajik

“…While traditional inspection and side-channel methods offer potential for tamper detection, they may not reliably detect all forms of attacks and often face practical limitations in terms of scalability, accuracy, or applicability. …”
Get full text

Hyperspectral Anomaly Detection: Comparative Evaluation in Scenes with Diverse Complexity by Dirk Borghys, Ingebjørg Kåsen, Véronique Achard, Christiaan Perneel

“…For that reason a variety of other anomaly detection methods have been developed. This paper examines three classes of anomaly detectors: subspace methods, local methods, and segmentation-based methods. …”
Get full text

Two distinct dynamic modes subtend the detection of unexpected sounds. by Jean-Rémi King, Alexandre Gramfort, Aaron Schurger, Lionel Naccache, Stanislas Dehaene

Get full text

Cross-Scenario Subdomain Adaptive Displacement Anomaly Detection in Dams by Yu Wang, Guohua Liu

“…This study presents the first application of subdomain adaptation for cross-scenario anomaly detection in dams, addressing distribution shifts across varying operational conditions. …”
Get full text

Community Detection in Social Network Based on Node Influence Expansion by YANG Hailu, ZHAO Xin, CHEN Chen, WANG Lili

“…To begin with, the local influence of nodes is computed using the Monte Carlo approximation. …”
Get full text

Impedance Spectrum Measurement and Fault Detection for XLPE Coaxial Cables by LIU Chunqi, LI Shufeng, HUANG Yu, CHEN Dongsheng

“…By establishing a baseline to improve the discrimination rate of fault defects, the fault information of the same cable is detected from the first and last ends respectively, and the distance between the two opposite-direction extreme points within the local range of the maximum jump point is taken as the fault length. …”
Get full text

Design and Analysis of an Expert System for the Detection and Recognition of Criminal Faces by Rishi Gupta, Amit Kumar Gupta, Deepak Panwar, Ashish Jain, Partha Chakraborty

“…In this study, they were analyzed and compared with the many methods of face detection and face recognition, such as HAAR cascades, local binary patterns histogram, support vector machines, convolutional neural networks, and ResNet-34. …”
Get full text

Comparison of Various Feature Extractors and Classifiers in Wood Defect Detection by Kenan Kiliç, Kazım Kiliç, İbrahim Alper Doğru, Uğur Özcan

“…The findings show that the most effective features in detecting defective wood are extracted by the Local Binary Pattern (LBP) method and the most effective classifier is the Random Forest Algorithm. …”
Get full text

Non-invasive vital parameter detection using neuromorphic cameras by Huhs Niklas, Kalashtari Niloofar, Kraitl Jens, Hornberger Christoph, Simanski Olaf

“…The respiration rate was detected with a mean absolute error of 0.66 bpm. The heart rate was detected with an accuracy of 95 % and a mean absolute error of less than 2 bpm. …”
Get full text

DCW-YOLO: Road Object Detection Algorithms for Autonomous Driving by Hongge Ren, Fangke Jing, Song Li

“…Aiming at the problems of multiple parameters and poor detection accuracy of object detection network in automatic driving scenarios, an object detection algorithm based on improved YOLOv8 is proposed. …”
Get full text