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total: 60
Search results for: CNN ROBUSTNESS DETECTION UNCERTAINTY
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Development of an orbital shaker-assisted fatty acid-based switchable solvent microextraction procedure for rapid and green extraction of amoxicillin from complex matrices: Central composite design
PublicationIn this study, a cheap, fast and simple orbital shaker-assisted fatty acid-based switchable solvent microextraction (OS-FASS-ME) procedure was developed for the extraction of amoxicillin (AMOX) in dairy products, pharmaceutical samples and wastewater prior to its spectrophotometric analysis. Fatty acid-based switchable solvents were investigated for extracting AMOX. The key factors of the OS-FASS-ME procedure were optimized using...
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Optimization of vortex-assisted hydrophobic magnetic deep eutectic solvent-based dispersive liquid phase microextraction for quantification of niclosamide in real samples
PublicationIn this manuscript, a green and fast vortex-assisted hydrophobic magnetic deep eutectic solvent-based dispersive liquid phase microextraction (VA-HMDES-DLPME) method was developed for the selective extraction and determination of niclosamide in read samples, including rice, medicine tablets, and water samples. Here, hydrophobic magnetic deep eutectic solvents were used as the extracting solvent without requiring any centrifugation...
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Combination of homogeneous liquid–liquid extraction and vortex assisted dispersive liquid–liquid microextraction for the extraction and analysis of ochratoxin A in dried fruit samples: Central composite design optimization
PublicationThis paper presents a new analytical procedure based on combination of homogeneous liquid–liquid extraction (HLLE) and vortex-assisted dispersive liquid–liquid microextraction (VA-DLLME) for the accurate and reliable determination of ochratoxin A (OTA) in dried fruit samples. To enable selective extraction of the OTA, six hydrophobic deep eutectic solvents (hDESs) were prepared and tested as extraction solvents. Optimization of...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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An Instantaneous Engine Speed Estimation Method Using Multiple Matching Synchrosqueezing Transform
PublicationInstantaneous rotational speed measurement of the engine is crucial in routine inspection and maintenance of an automobile engine. Since the contact measurement of rotational speed is not always available, the vibration measurement has been used for noncontact rotational speed estimation methods. Unfortunately, the accuracy of the noncontact estimation methods by analyzing engine vibration frequency is not satisfactory due to the...
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Synthesis, characterization and application of cross-linked functional terpolymer through epoxy group as sorbent for extraction of cadmium from waters and foods: Multivariate optimization
PublicationThe purpose of this study was to develop a selective sorbent for cadmium ions (Cd(II)) enrichment in orbital shaker assisted solid phase microextraction (OS-SPME) from different aqueous and food samples. A maleic anhydride-styrene-glycidyl methacrylate (MA-St-GMA) terpolymer was synthesized and characterized in detail. Experimental variables of sample preparation step were optimized using a central composite design (CCD). The final...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
PublicationWetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...