Suggested Topics within your search.
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Enzymes and Their Forms Used in Detection of Organophosphorus Compounds
Published 2021-06-01“…The most technologically advanced solution that is close to the practical implementation seems to be bioanalytical systems using immobilized enzymes. Improving the detection limits of the OPC can be achieved by using nanoobjects together with modern methods of signal transducers, for example, with nanomechanical detectors and signal converters. …”
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Hybrid Technique Used for Straight Line Detection
Published 2011-07-01“…Many techniques have been used in this research to detect straight line in digital image on the same samples. …”
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Radiotracers Used for the Scintigraphic Detection of Infection and Inflammation
Published 2015-01-01Get full text
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Comparison of methods for detecting mandibular lingula and can antilingula be used in lingula mandibula detection?
Published 2025-03-01“…Abstract Objective The aim of this study is to evaluate the relationship between anatomical reference points used during orthognathic surgery and to minimize the risks of iatrogenic neurovascular damage. …”
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Diagnostic Accuracy of Methods Used to Detect Cracked Teeth
Published 2025-06-01“…The primary objective of this study was to determine the diagnostic accuracy of four commonly used visual tests in diagnosing cracked teeth based on clinical appearance, independent of patient symptoms. …”
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Novel PCR-Based Technology for the Detection of Sunflower in Edible and Used Cooking Oils
Published 2024-11-01Subjects: “…sunflower detection…”
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A Review of the Monitoring Techniques Used to Detect Oestrus in Sows
Published 2025-01-01“…The agricultural industries have embraced the use of technologies as they improve efficiency and food security. …”
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Consumers’ Knowledge of Food Adulteration and Commonly Used Methods of Detection
Published 2022-01-01“…This study identifies the degree of adulteration in some commonly used food items bought by consumers and the means of detection. …”
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Algorithm Used to Detect Weak Signals Covered by Noise in PIND
Published 2019-01-01“…PIND (particle impact noise detection) is the most commonly used method for the detection of loose particles in the aerospace electronic components. …”
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A Comprehensive Analysis of Fake News Detection Models: A Systematic Literature Review and Current Challenges
Published 2023-12-01“…Our study focuses on how machine learning and deep learning algorithms are used to detect fraudulent data. The most fundamental and practical techniques deployed over recent years are investigated, classified, and defined in numerous datasets in an extended review model. …”
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The manipulation of odor availability of training aids used in detection canine training
Published 2025-01-01“…Historically, and a point of ongoing contention, detection canine threshold (i.e., sensitivity or limit of detection) training has primarily focused on changing the weight of the training aid substance used. …”
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Detection of sensors used for adversarial examples against machine learning models
Published 2024-12-01“…This study introduces a novel detection method using a feature-removable model (FRM), which allows the selective removal of features to identify inconsistencies in the model's outputs when different sensor features are altered. …”
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Automatic beams detection used for LiFi car-2-car communication
Published 2020-09-01Get full text
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Impact of Leg Position on Measurements Used to Detect Femoral Component Subsidence in THA
Published 2024-12-01“…Background: A fully automated artificial intelligence–based tool was developed to detect and quantify femoral component subsidence between serial radiographs. …”
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Diagnostic Methods Used in Detecting Syphilis in Paleopathological Research—A Literature Review
Published 2025-04-01Get full text
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Gel clot assay used for detection of candida spp onfection in urinary tract
Published 2006-03-01Get full text
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Anomaly detection and removal strategies for in-line permittivity sensor signal used in bioprocesses
Published 2025-07-01“…However, our method provides a structured solution through three consecutive steps: 1) Signal preprocessing to reduce noise and eliminate context dependency; 2) Anomaly detection using threshold-based identification; 3) Validation and removal of identified anomalies.Results and discussionWe demonstrate that our approach effectively detects and removes anomalies by compensating signal shift value, while remaining computationally efficient and practical for real-time use. …”
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Automatic ovarian follicle detection using object detection models
Published 2024-12-01“…In this work, we show the benefits of deep learning models for counting antral follicles and corpus lutea in ovarian histology sections. Here, we use various backbone architectures to build two one-stage object detection models, i.e. …”
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