[PDF] Top 20 Sistema de precedentes judiciais na Justiça do Trabalho
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Medicare fraud detection using neural networks
... artificial neural network (ANN) with two or more hidden layers to approxi- mate some function f ∗ , where f ∗ can be used to map input data to new representations or make predictions ...biological neural ... See full document
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Detection of Fraud Transactions Using Recurrent Neural Network during COVID-19
... related fraud detection ...statement fraud from a selection of Greek manufacturing firms using Decision Tree, Neural networks, Bayesian belief networks with an efficiency ... See full document
8
Credit Card Fraud Discovery: A Survey
... card fraud detection can be done with the help of neural networks ...(neural networks) on the basis of the attributes of a credit card ...similarly neural networks ... See full document
13
Credit Card Fraud Identification Using Artificial Neural Networks
... card fraud results the financial losses of organizations and also affects the individual user, if the credit card details get ...many fraud prevention strategies such as credit card authorization, address ... See full document
12
Knowledge Discovering in Corporate Securities Fraud by Using Grammar Based Genetic Programming
... of fraud by applying different statistical and Artificial Intelligence (AI) data mining ...securities fraud detection, which are Logistic regression model, Neural Networks (NNs), ... See full document
5
Informative Feature Trained Classification System For Credit Card Fraud Detection
... artificial neural networks, capable of acting as universal ...both neural networks, and fuzzy logic systems to approximate each other as ...Both neural networks and fuzzy logic ... See full document
7
Steganography Detection using Functional Link Artificial Neural Networks
... Artificial Neural Network to detect the coded ...forward neural network and to overcome the linear mapping, functionally expands the input ...of neural networks using JPEG ...the ... See full document
83
Performance Evaluation of Genetic Algorithm and Counter Propagation Neural Network for Anomaly Detection in Online Transaction
... propagation neural network to detect anomalies in an online ...evaluated using evaluation metrics to know which technique will perform better than the other in credit card fraud detection in ... See full document
41
Fraud Detection of the Mobile Apps Using Leading Minining Sessions
... by using so-called “bot farms” or “human water armies” to inflate the App downloads, ratings and reviews in a very short ...ranking fraud raises great concerns to the mobile App ...ranking fraud [3] ... See full document
14
Training and classification of Epilepsy Detection using EEG
... other neural networks today use gradual linear progression functions to ease an NN into its proper behavior, some researchers use genetic algorithms to evolve ...tested using the same set of test ... See full document
9
Fungus Detection using Convolutional Neural Networks
... In [1], The fungus is the big hazard and farmers lost nearly a million dollars per year due to different varieties of species in fungus. An automated system for the detection of fungus in the air spores. Air ... See full document
56
Face Recognition and Feature Detection Using Artificial Neural Networks and ANFIS
... The experiment has been conducted on a 50 individuals. Each individual has three views and each view has 3 samples. Their images have been taken under constant light so as to ensure that their all three views look alike. ... See full document
5
FPGA Implementation of Glaucoma Detection using Neural Networks
... disease detection from retinal images using artificial neural network as the ...of neural network offers both the adaptability in reconfiguration and parallel architecture of ...the ... See full document
68
Download Download PDF
... “healthcare fraud”, “healthcare abuse”, “fraud, waste and abuse in healthcare”, “techniques for fraud detection in healthcare”, benefits of fraud detection methods in healthcare” ... See full document
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ISSN: 2321-8363 Impact Factor: 5.515
... Cross-validation tests for 3, 5, 7, and 10 folds were performed for each algorithm (COS-P, COS-P-Map, COS-P-Poly and COS-Radial) on the training dataset. For each algorithm, we used the best result from maximum 100 ... See full document
10
Token Level Metaphor Detection using Neural Networks
... done using various fine-grained tags; however, we only use the most clear cut tag mrw (metaphor-related word), label- ing everything else as ...the detection of metaphoricity of con- tent tokens is of ... See full document
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Fraud Detection of the Mobile Apps Using Leading Minining Sessions
... Ranking fraud in the mobile App market refers to fraudulent or deceptive activities which have a purpose of bumping up the Apps in the popularity ...ranking fraud. While the importance of preventing ranking ... See full document
86
Virus Detection using Artificial Neural Networks
... In Phase 1, the Training Data, which comprises of two types of executable files-legitimate and virus infected, is given as input to the Feature Extractor. The Feature Extractor takes a one feature (PE Structure field) at ... See full document
240
Brain Tumor Classification Using Convolutional Neural Networks
... The brain tumors, are the most common and aggressive disease, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of patients. Generally, ... See full document
5
Detection and Recognition of Vehicle Using Neural Networks
... road networks is largely dependent on the assumption of a known traffic model in the ...highway networks based on real-world highway tollgate data that reflect the highway's characteristics, such as ... See full document
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