Study on the identification and classification of fish is challenging and valuable because of its role in advancing the marine and agricultural fields. This research has benefits interms of monitoring fish populations...
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We propose a method for Vietnamese Sign Language (VSL) recognition using a fusion of RGB and Depth information based on the Inflated 3D ConvNet (I3D) architecture. Our approach applies I3D feature extraction independe...
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In this paper, we tackle the challenge of improving both user capacity and power allocation in wireless networks with sub-channel assignment constraints. We start by generating channel data using the Shannon capacity ...
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Despite recent advances in face recognition using deep learning, pose changes are still one of the challenging problems. In this paper, we presented a method to normalize the image in the feature space by capturing lo...
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Our work, as 3D Audio Working Group of Web3D Consortium, aims to integrate acoustic properties associated with geometric shapes together with 3D spatial sound and insert this new technology into the X3D v4.0 ISO stand...
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The present paper proposes an experimental test rig and methodology for the optical evaluation of micro-contact parameters in the case of micro-indentation tests of elastic materials with rigid indenters. Micro-contac...
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Online transactions have transformed commerce and international trade but have brought up new difficulties, especially regarding fraud detection and security. The exponential rise in digital transactions has made reli...
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ISBN:
(数字)9798331541217
ISBN:
(纸本)9798331541224
Online transactions have transformed commerce and international trade but have brought up new difficulties, especially regarding fraud detection and security. The exponential rise in digital transactions has made reliable fraud detection systems using machine learning and artificial intelligence techniques which are leveraged to detect and mitigate fraud thereby increasing the security of transactions. The paper suggested a model in which data preprocessing using standard scalar along with SMOTE for data balancing is proposed. Data is split into 80-20% train test data based on credit card transactions. An artificial neural network is used to determine credit card fraud. Activation function followed by batch normalization blended with Adam Optimizer and cross-entropy is used to process the computation. Furthermore, classification parameters obtained an Accuracy of 99.95%, Precision of 99%, Recall of 99%, and F1Score of 99%. The result obtained by the proposed method outperforms the existing approach that focuses on secured transactions and helps both the client and server.
The analysis of non-stationary and non-periodic signals has long been restricted to Fourier decomposition in the frequency domain. However, when bringing the frequency content to the time domain (STFT), harmonics appe...
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Efficient waste management together with certain measures to promote the recycling process are essential for over-coming global environmental issues. In this study, we describe Repro an app, which is targeted at trans...
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ISBN:
(数字)9798350349719
ISBN:
(纸本)9798350349726
Efficient waste management together with certain measures to promote the recycling process are essential for over-coming global environmental issues. In this study, we describe Repro an app, which is targeted at transforming how we collect waste and recycle by integrating CNN technology and a reward-based system. Users, with the Repro app, take pictures of any trash they discard and rely on the underlying CNN model to identify the type of trash correctly. If a user's trash accumulation reaches beyond a given limit the system sends a notification to the trash collectors via the riders app to direct for a timely waste collection. User tokens are provided to users after trash collection, which can be redeemed within the Repro app for various product items and coupons. Moreover, this motivating approach encourages responsible waste management which goes along with the development of environmental custodianship among users. We describe the technical implementation of the CNN-based framework, assess the performance of the level of waste classification accuracy, and predict the behavioral implications of the reward system on recycling behavior. The study illustrates that Repro is a scalable solution for smarter waste collection and recycling endeavors, consequently creating a more eco-minded and sustainable environment.
Feature selection is an expensive challenging task in machine learning and data mining aimed at removing irrelevant and redundant features. This contributes to an improvement in classification accuracy, as well as the...
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