Wyniki wyszukiwania dla: INSTANCE SEGMENTATION,SYNTHETIC DATASET,DEEP LEARNING
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Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublikacjaVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
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Selection of DES for biotrickling filtration of air polluted with hexane and cyclohexane
Dane BadawczeDataset covers selected data collected during selection of deep eutectic solvent (DES) additive to mineral salt medium (MSM) as a liquid phase during biotrickling filtration of air polluted with hexane and cyclohexane.
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublikacjaAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
PublikacjaCognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...
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IFE: NN-aided Instantaneous Pitch Estimation
PublikacjaPitch estimation is still an open issue in contemporary signal processing research. Nowadays, growing momentum of machine learning techniques application in the data-driven society allows for tackling this problem from a new perspective. This work leverages such an opportunity to propose a refined Instantaneous Frequency and power based pitch Estimator method called IFE. It incorporates deep neural network based pitch estimation...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublikacjaThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Improving Accuracy of Respiratory Rate Estimation by Restoring High Resolution Features With Transformers and Recursive Convolutional Models
PublikacjaNon-contact evaluation of vital signs has been becoming increasingly important, especially in light of the COVID- 19 pandemic, which is causing the whole world to examine people’s interactions in public places at a scale never seen before. However, evaluating one’s vital signs can be a relatively complex procedure, which requires both time and physical contact between examiner and examinee. These re- quirements limit the number...
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XRD patterns of V2O5 thin films deposited on isotropic etching silicon substrates (111)
Dane BadawczeThe DataSet contains the XRD patterns of V2O5 thin films deposited on isotropic etching silicon substrates (111). The silicon wafers were etched in a mixture of nitric acid, hydrofluoric acid, and acetic acid in the ratio of 40:1:15. The soaking time for the substrates was from 30 to 90 seconds. The thin films were obtained by the sol-gel method. ...
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Investigating Noise Interference on Speech Towards Applying the Lombard Effect Automatically
PublikacjaThe aim of this study is two-fold. First, we perform a series of experiments to examine the interference of different noises on speech processing. For that purpose, we concentrate on the Lombard effect, an involuntary tendency to raise speech level in the presence of background noise. Then, we apply this knowledge to detecting speech with the Lombard effect. This is for preparing a dataset for training a machine learning-based...
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A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublikacjaTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
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The luminescence study of (C10H16N)2MnBr4 Organic–Inorganic Hybrid
Dane BadawczeOrganic–inorganic hybrid metal halides have recently attracted attention in the global research field for their bright light emission, tunable photoluminescence wavelength, and convenient synthesis method. This study reports the detailed properties of (C10H16N)2MnBr4, which emits bright green light with a high photoluminescence quantum yield. Results...
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Thermal behavior of TeOx xerogel powder under different atmospheres
Dane BadawczeThe DataSet contains the results of the thermal behavior of the TeOx xerogel powder measured under different atmospheres. The material was obtained by the sol-gel method. The starting solution was prepared by mixing telluric acid (precursor) with thetraetylene glycol, water, and ethanol. The sol was obtained by vigorously stirring precursor solution...
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SEM micrographs of V2O5 thin films deposited on isotropic etching silicon substrates (111)
Dane BadawczeThe DataSet contains the scanning electron microscopy (SEM) micrographs of V2O5 thin films deposited on isotropic etching silicon substrates (111). The silicon wafers were etched in a mixture of nitric acid, hydrofluoric acid, and acetic acid in the ratio of 40:1:15. The soaking time for the substrates was from 30 to 90 seconds. The thin films were...
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Cascade Object Detection and Remote Sensing Object Detection Method Based on Trainable Activation Function
PublikacjaObject detection is an important process in surveillance system to locate objects and it is considered as major application in computer vision. The Convolution Neural Network (CNN) based models have been developed by many researchers for object detection to achieve higher performance. However, existing models have some limitations such as overfitting problem and lower efficiency in small object detection. Object detection in remote...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublikacjaThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublikacjaThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Artificial intelligence for software development — the present and the challenges for the future
PublikacjaSince the time when first CASE (Computer-Aided Software Engineering) methods and tools were developed, little has been done in the area of automated creation of code. CASE tools support a software engineer in creation the system structure, in defining interfaces and relationships between software modules and, after the code has been written, in performing testing tasks on different levels of detail. Writing code is still the task...
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Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublikacjaThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublikacjaThe purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...
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Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework
PublikacjaThe rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between...
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Empirical analysis of tree-based classification models for customer churn prediction
PublikacjaCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Thermal behavior of VO2/V2O3 nanostructures obtained at 500°C under argon atmosphere
Dane BadawczeThe DataSet contains the results of the thermal behavior of the VO2/V2O3 nanostructures. The vanadium oxides nanostructures were synthesized by the sol-gel method, where obtained xerogel powder was annealing at 500°C under an argon atmosphere. The information about xerogel powder synthesis is described in the Journal of Nanomaterials.
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Thermal behavior of VO2/V2O3 nanostructures obtained at 1000°C under argon atmosphere
Dane BadawczeThe DataSet contains the results of the thermal behavior of the VO2/V2O3 nanostructures. The vanadium oxides nanostructures were synthesized by the sol-gel method, where obtained xerogel powder was annealing at 1000°C under an argon atmosphere. The information about xerogel powder synthesis is described in the Journal of Nanomaterials.
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Thermal behavior of VO2/V2O3 nanostructures obtained at 650°C under reducing atmosphere
Dane BadawczeThe DataSet contains the results of the thermal behavior of the VO2/V2O3 nanostructures. The vanadium oxides nanostructures were synthesized by the sol-gel method, where obtained xerogel powder was annealing at 650°C under a reducing atmosphere (95% Ar 5% H2). The information about xerogel powder synthesis is described in the Journal of Nanomaterials.
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Thermal behavior of VO2/V2O3 nanostructures obtained at 400°C under argon atmosphere
Dane BadawczeThe DataSet contains the results of the thermal behavior of the VO2/V2O3 nanostructures. The vanadium oxides nanostructures were synthesized by the sol-gel method, where obtained xerogel powder was annealing at 400°C under an argon atmosphere. The information about xerogel powder synthesis is described in the Journal of Nanomaterials.
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Thermal behavior of VO2/V2O3 nanostructures obtained at 700°C under argon atmosphere
Dane BadawczeThe DataSet contains the results of the thermal behavior of the VO2/V2O3 nanostructures. The vanadium oxides nanostructures were synthesized by the sol-gel method, where obtained xerogel powder was annealing at 700°C under an argon atmosphere. The information about xerogel powder synthesis is described in the Journal of Nanomaterials.
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Thermal behavior of TeOx powder
Dane BadawczeThe DataSet contains the results of the thermal behavior of the TeOx powder. The material was obtained by the sol-gel method. The starting solution was prepared by mixing telluric acid (precursor) with thetraetylene glycol, water, and ethanol. The sol was obtained by vigorously stirring precursor solution at 50°C for 2h, then the temperature was raised...
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Thermal behavior of VO2/V2O3 nanostructures obtained at 800°C under argon atmosphere
Dane BadawczeThe DataSet contains the results of the thermal behavior of the VO2/V2O3 nanostructures. The vanadium oxides nanostructures were synthesized by the sol-gel method, where obtained xerogel powder was annealing at 800°C under an argon atmosphere. The information about xerogel powder synthesis is described in the Journal of Nanomaterials.
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Thermal behavior of VO2/V2O3 nanostructures obtained at 600°C under argon atmosphere
Dane BadawczeThe DataSet contains the results of the thermal behavior of the VO2/V2O3 nanostructures. The vanadium oxides nanostructures were synthesized by the sol-gel method, where obtained xerogel powder was annealing at 600°C under an argon atmosphere. The information about xerogel powder synthesis is described in the Journal of Nanomaterials.
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Computational Complexity and Its Influence on Predictive Capabilities of Machine Learning Models for Concrete Mix Design
PublikacjaThe design of concrete mixtures is crucial in concrete technology, aiming to produce concrete that meets specific quality and performance criteria. Modern standards require not only strength but also eco-friendliness and production efficiency. Based on the Three Equation Method, conventional mix design methods involve analytical and laboratory procedures but are insufficient for contemporary concrete technology, leading to overengineering...
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Equal Baseline Camera Array—Calibration, Testbed and Applications
PublikacjaThis paper presents research on 3D scanning by taking advantage of a camera array consisting of up to five adjacent cameras. Such an array makes it possible to make a disparity map with a higher precision than a stereo camera, however it preserves the advantages of a stereo camera such as a possibility to operate in wide range of distances and in highly illuminated areas. In an outdoor environment, the array is a competitive alternative...
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Karol Flisikowski dr inż.
OsobyKarol Flisikowski jest profesorem uczelni w Katedrze Statystyki i Ekonometrii, Wydziału Zarządzania i Ekonomii Politechniki Gdańskiej. Jest odpowiedzialny jest za prowadzenie zajęć ze statystyki opisowej i matematycznej (w języku polskim i angielskim), a także badań naukowych w zakresie statystyki społecznej. Był uczestnikiem wielu konferencji o zasięgu krajowym, jak i międzynarodowym, gdzie prezentował wyniki prowadzonych przez...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublikacjaHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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The assessment of microbiological antimicrobial properties of PE film loaded with nanozinc filler
Dane BadawczeThe dataset contains the results of a single series of determinations of the antimicrobial properties against E. coli and S. aureus of polyethylene films containing the nanozinc filler.
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublikacjaThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Metal–Organic Frameworks (MOFs) for Cancer Therapy
PublikacjaMOFs exhibit inherent extraordinary features for diverse applications ranging from catalysis, storage, and optics to chemosensory and biomedical science and technology. Several procedures including solvothermal, hydrothermal, mechanochemical, electrochemical, and ultrasound techniques have been used to synthesize MOFs with tailored features. A continued attempt has also been directed towards functionalizing MOFs via “post-synthetic...
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Electrochemical impedance spectroscopy measurements - conductivity vs. temperature and conductivity vs. oxygen partial pressure - BaCe0.6Zr0.2Y0.1Tb0.1O3-δ
Dane BadawczeThe dataset consists of two main catalogs consisting of measurement data: of the electrical conductivity of the BaCe0.6Zr0.2Y0.1Tb0.1O3-δ (BCZYTb) sample as a function of temperature and of the electrical conductivity as a function of oxygen partial pressure (pO2). Measurements as a function of temperature were carried out in dry and wet air (pH2O ~...
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The corrosion studies of 3,4,5-trihydroxybenzoic acid as an effective corrosion inhibitor of low alloy steel
Dane BadawczeThe dataset contains the electrochemical studies evaluating if gallic acid is a corrosion inhibitor for low alloy steel. Three measurements were carried out each case; corrosion potential (label ecorr), electrochemical impedance spectroscopy (label eis) and cyclic polarization (label cp). The measurements were carried out in sodium chloride, acidified...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublikacjaIntroduction: 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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Experience-Oriented Intelligence for Internet of Things
PublikacjaThe Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. The main reason behind this interest is the capabilities of the IoT for seamlessly integrating classical networks and networked objects, and hence allows people to create an intelligent environment based on this powerful integration. However, how to extract useful information from data produced by IoT and facilitate...
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Sensors and System for Vehicle Navigation
PublikacjaIn recent years, vehicle navigation, in particular autonomous navigation, has been at the center of several major developments, both in civilian and defense applications. New technologies, such as multisensory data fusion, big data processing, or deep learning, are changing the quality of areas of applications, improving the sensors and systems used. Recently, the influence of artificial intelligence on sensor data processing and...
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High-quality academic teachers in business school. The case of The University of Gdańsk, Poland
PublikacjaThe Bologna process, the increasing number of higher education institutions, the mass education and the demographic problems make the quality of education and quality of the academic teachers a subject of wide public debate and concern. The aim of the paper is to identify the most preferred characteristics of a teacher working at a business school. The research problem was: What should a high-quality business school academic teacher...
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Sathwik Prathapagiri
OsobySathwik was born in 2000. In 2022, he completed his Master’s of Science in Biological Sciences and Bachelor’s of Engineering in Chemical Engineering in an integrated dual degree program from Birla Institute Of Technology And Science, Pilani, India. During his final year, he worked as a research intern under Dr Giri P Krishnan at Bazhenov lab, University of California San Diego school of medicine to pursue his Master’s Thesis on...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublikacjaThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublikacjaDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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Adaptacyjny system sterowania ruchem drogowym
PublikacjaAdaptacyjny system sterowania ruchem drogowym to rodzaj systemu sterowania, który dynamicznie, w czasie rzeczywistym, dostosowuje swoje parametry w oparciu o bieżące warunki ruchu drogowego. Celem niniejszej rozprawy jest sprawdzenie wpływu wybranych cech systemu, zbudowanego w oparciu o zaprojektowane i zbudowane z udziałem autora inteligentne znaki drogowe, na wybrane parametry mające wpływ na bezpieczeństwo i płynność ruchu....
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublikacjaWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...