Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
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Deniable Authentication Encryption for Privacy Protection using Blockchain
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Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
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Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
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QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
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Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach
Volume-3 | Issue-1
Multi-scale CNN Approach for Accurate Detection of Underwater Static Fish Image
Volume-3 | Issue-3
Real Time Anomaly Detection Techniques Using PySpark Frame Work
Volume-2 | Issue-1
Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3
Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4
Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3
Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing
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Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4
Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4
Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach
Volume-3 | Issue-4
ARTIFICIAL INTELLIGENCE APPLICATION IN SMART WAREHOUSING ENVIRONMENT FOR AUTOMATED LOGISTICS
Volume-1 | Issue-2
Deep Convolution Neural Network Model for Credit-Card Fraud Detection and Alert
Volume-3 | Issue-2
Volume - 2 | Issue - 2 | june 2020
Published
16 May, 2020
Verification of font style followed in a file is a difficult task to classify. An artificial intelligence based algorithm network can effectively perform this task in reduced time. Capsule network is one among such algorithm and an emerging technique implemented for so many classification process with limited datasets. The proposed font style classification algorithm is enforced with Capsule Network (CapsNet) algorithm for executing the font style classification task. The proposed method is confirmed by classifying times new roman, Arial black and Algerian font style in English letters along with the performance evaluation in terms of accuracy and confusion matrix parameters. The proposed network structure is also compared with the existing Naive Bayes (NB), Decision Tree (DT) and K nearest neighbor (KNN) algorithms for comparative study and the evaluation result indicates that the proposed font style classification model based on CapsNet is classifying the images with better accuracy, F1 score and Gmean.
KeywordsCapsule network font classification F1 score
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