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Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022).

Bibliographic Details
Main Author: Manza, Ramesh.
Other Authors: Gawali, Bharti., Yannawar, Pravin., Juwono, Filbert.
Format: eBook
Language:English
Published: Dordrecht : Atlantis Press (Zeger Karssen), 2023.
Edition:1st ed.
Series:Advances in Intelligent Systems Research Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Preface
  • Organization
  • Contents
  • Peer-Review Statements
  • 1 Review Procedure
  • 2 Quality Criteria
  • 3 Key Metrics
  • An Improved Computer Aided System for Lung Cancer Detection using Image Processing Techniques
  • 1 Introduction
  • 2 Literature survey
  • 3 Methodology
  • 4 Result
  • 5 Conclusion
  • References
  • Automated Detection of Tuberculosis Based on Cantilever Biosensor
  • 1 Introduction
  • 2 Bio-Mems Cantilever Sensor
  • 3 Experimental Details
  • 4 Result and Discussion
  • References
  • Diagnosing Microscopic Blood Samples for Early Detection of Leukemia by Deep and Hybrid Learning Techniques
  • 1 Introduction
  • 2 Related Work
  • 3 Materials and Methods
  • 3.1 Description of Two Datasets
  • 3.2 Pre-processing
  • 3.3 Convolutional Neural Networks (CNN)
  • 3.4 Hybrid of Deep and Machine Learning
  • 4 Experimental Result
  • 4.1 Splitting Dataset
  • 4.2 Evaluation Metrics
  • 4.3 CNN Models Results
  • 4.4 Results of the Hybrid CNN with SVM Algorithm
  • 5 Discussion
  • 6 Conclusion
  • References
  • Lung Cancer Nodules Detection Using Ideal Features Extraction Technique in CT Images
  • 1 Introduction
  • 2 Related Work
  • 3 Methods and materials
  • 3.1 Dataset
  • 3.2 Image Preprocessing
  • 3.3 Segmentation
  • 3.4 Feature Extraction
  • 3.5 Classification Using Hybrid-CNN
  • 4 Result and Discussion
  • 5 Conclusion
  • References
  • Fuzzy Level Set Search and Rescue Optimization (FLSSR) Based Segmentation of Pediatric Brain Tumor
  • 1 Introduction
  • 2 Related Work
  • 3 Proposed Methodology
  • 3.1 Preprocessing
  • 3.2 Fuzzy Level Set Search and Rescue Optimization (FLSSR) for Segmentation Process:
  • 4 Results and Discussions
  • 5 Performance Evaluation
  • 6 Conclusion
  • References
  • Investigating EEG Images of Cognitive Actions for Robotic Arm
  • 1 Introduction
  • 2 Literature Review
  • 3 Methodology
  • 3.1 Participants.
  • 3.2 Technical Analysis
  • 3.3 Analyzing .edf Files via EEGLAB
  • 3.4 Robotic Arm Overview
  • 3.5 Active Region Identification
  • 3.6 ERD and ERS for the Components in Frontal Region
  • 4 Performance evaluation of the Robotic Arm
  • 5 Result
  • 6 Conclusion
  • References
  • Localization of Intervertebral Discs Using Deep-Learning and Region Growing Technique
  • 1 Introduction
  • 2 Review of the Literature
  • 3 Proposed Methodology
  • 3.1 Data
  • 3.2 Pre-processing
  • 3.3 Proposed Method
  • 4 Results and Discussion
  • 4.1 Evaluation Matrices
  • 4.2 Effect of Hourglass Attention Mechanism
  • 5 Conclusion
  • References
  • Identification of Skin Disease Using Machine Learning
  • 1 Introduction
  • 2 Related Works
  • 3 Method and Techniques
  • 3.1 Input Images
  • 3.2 Image Preprocessing
  • 3.3 Filtering Techniques
  • 3.4 Gaussian Filter
  • 3.5 Image Segmentation
  • 3.6 Support Vector Machine (SVM)
  • 3.7 K-nearest Neighbor (KNN)
  • 3.8 Feature Extraction
  • 3.9 Color Moments
  • 3.10 Texture Feature Extraction
  • 4 Performance Measures
  • 5 Result and Discussion
  • 6 Conclusion
  • References
  • Apple Classification Based on MRI Images Using VGG16 Convolutional Deep Learning Model
  • 1 Introduction
  • 2 Literature Survey
  • 3 Materials and Methods
  • 3.1 Dataset
  • 3.2 VGG Model
  • 4 Results and Discussion
  • 5 Conclusion and Future Work
  • References
  • Design a Novel Detection Using KNN Classification Technique for Early Sign of Diabetic Maculopathy
  • 1 Introduction
  • 2 Methodology
  • 2.1 Preprocessing
  • 2.2 RGB Channel
  • 2.3 Histogram
  • 2.4 Enhancement
  • 2.5 KNN Classification
  • 3 Experiment Result
  • 4 Conclusion
  • References
  • Extraction of Bank Cheque Fields Based on Faster R-CNN
  • 1 Introduction
  • 2 Related Work and Overview
  • 2.1 Related Work
  • 2.2 Faster RCNN
  • 3 Methodology
  • 3.1 ConvNet Layers
  • 3.2 Region Proposal Networks.
  • 3.3 Region of Interest Pooling Layer
  • 3.4 Classification Layers
  • 4 Experiment and Results
  • 4.1 Dataset
  • 4.2 Experiment Results
  • 5 Conclusion
  • References
  • Multimodal Deep Learning Based Score Level Fusion Using Face and Fingerprint
  • 1 Introduction
  • 2 Literature Survey
  • 3 About Database
  • 4 Experimental Setup
  • 5 Proposed Methodology
  • 5.1 Pre-processing
  • 5.2 CNN
  • 5.3 VGG16
  • 5.4 Features Classification
  • 5.5 Score Level Fusion
  • 6 Performance Analysis
  • 6.1 Classification and Confusion Matrix
  • 7 Result and Discussion
  • 8 Conclusion
  • 9 Contributions
  • References
  • Enhanced Technique for Exemplar Based Image Inpainting Method
  • 1 Introduction
  • 2 Literature Review
  • 3 Methodology
  • 3.1 Input Image
  • 3.2 Perform Cropping
  • 3.3 Perform Inpainting by Criminisi Method
  • 3.4 Finding Parameters
  • 3.5 Perform Tensor Inpainting
  • 4 Experimental Results
  • 5 Conclusion
  • References
  • An Optimal (2, 2) Visual Cryptography Schemes For Information Security
  • 1 Introduction
  • 2 Literature Review
  • 3 Methodology
  • 4 Experimental Result
  • 5 Discussion and Performance Analysis
  • 5.1 Pixel Expansion
  • 5.2 Contrast and Statistical Analysis
  • 5.3 Mean Square Error
  • 5.4 Peak-Signal-to-Noise-Ratio
  • 5.5 Universal-Index-Quality (UIQ)
  • 5.6 Maximum Difference (MD)
  • 5.7 Average Difference (AD)
  • 6 Conclusion
  • References
  • A Numeral Script Identification from a Multi-lingual Printed Document Image
  • 1 Introduction
  • 1.1 Motivation
  • 2 Proposed Method
  • 3 Experimental Results
  • 4 Conclusion
  • References
  • A Novel Approach for Object Detection Using Optimized Convolutional Neural Network to Assist Visually Impaired People
  • 1 Introduction
  • 2 Related Work
  • 3 Architectural Description of the Proposed Object Detection Model for Visually Impaired (ODMVI)
  • 3.1 Preprocessing
  • 3.2 Segmentation.
  • 3.3 Feature Extraction
  • 4 Optimal Feature Selection
  • 5 Object Detection Using CNN
  • 5.1 Convolution Layer
  • 5.2 Pooling Layer
  • 5.3 Fully Connected Layer
  • 6 Dataset
  • 7 Results and Discussion
  • 7.1 Simulation Procedure
  • 7.2 Convergence Analysis
  • 7.3 Performance Evaluation of ODMVI
  • 8 Conclusion and Future Scope
  • References
  • A Machine Learning Based Approach for Image Quality Assessment of Forged Document Images
  • 1 Introduction
  • 2 Related Work
  • 3 Proposed Methodology
  • 3.1 Pre-processing
  • 3.2 Feature Extraction
  • 3.3 Classification
  • 4 Implementation and Results
  • 4.1 Dataset
  • 5 Statistical Test of Significance
  • 6 Conclusion
  • References
  • Comparative Study of Grid-Inverted List Hybrid Indexing Techniques for Moving Objects and Queries
  • 1 Introduction
  • 2 Related Work
  • 3 Methodology
  • 3.1 Grid-Inverted List Hybrid Index
  • 3.2 KNN Query
  • 3.3 Hybrid Index Implementation with YPK-CNN Technique
  • 3.4 Hybrid Index Implementation with SEA-CNN Technique
  • 3.5 Hybrid Index Implementation with CPM Technique
  • 3.6 Differences Between YPK-CNN, SEA-CNN and CPM Techniques
  • 3.7 Proposed Algorithms
  • 4 Experimental work
  • 5 Results and Discussion
  • 6 Conclusion
  • References
  • Text-Independent Source Identification of Printed Documents using Texture Features and CNN Model
  • 1 Introduction
  • 2 Review of Related Studies
  • 3 Proposed Method
  • 3.1 Data Collection
  • 3.2 Pre-processing
  • 3.3 Feature Extraction
  • 4 Experimental Results and Discussion
  • 4.1 Performance of Textual Features
  • 4.2 Deep Learning CNN Performance Measurement
  • 4.3 Comparison Analysis
  • 5 Conclusion
  • References
  • A Vision-Based Sign Language Recognition using Statistical and Spatio-Temporal Features
  • 1 Introduction
  • 2 Literature Review
  • 3 Proposed Methodology
  • 3.1 Data Collection
  • 3.2 Feature Extraction and Learning.
  • 4 Results and Discussion
  • 4.1 Raw Data Pre-processing
  • 4.2 Extraction and Analysis of Statistical and Spatio-Temporal Features
  • 4.3 Classification of Statistical Features
  • 4.4 Early Fusion of Statistical and Spatio-Temporal Features
  • 4.5 Comparison of Results
  • 4.6 Conclusion and Future Work
  • References
  • Single Image Dehazing Using Haze Veil Analysis and CLAHE
  • 1 Introduction
  • 2 Methodology
  • 3 Haze Veil Calculation
  • 3.1 Computing Reflectance Image
  • 4 Experimental Results
  • 5 Conclusion
  • References
  • HiTEK Multilingual Speech Identification Using Combinatorial Model
  • 1 Introduction
  • 2 Literature Review
  • 3 Challenges
  • 4 Methodology
  • 4.1 Hidden Markov Model- Gaussian Mixture Model
  • 4.2 Hidden Markov Model- Artificial Neural Networks
  • 4.3 Hidden Markov Model- Deep Neural Networks
  • 4.4 POS Tagging
  • 4.5 Tokenization and Stemming
  • 4.6 Morphological Analysis
  • 4.7 Syntactical Analysis
  • 4.8 Semantic Analysis
  • 4.9 Word Discourse Knowledge
  • 5 Experimental Setup and Results
  • 6 Conclusion and Future Scope
  • References
  • Devanagari License Plate Detection, Classification and Recognition
  • 1 Introduction
  • 1.1 Devanagari (Nepalese) License Plate
  • 2 Literature Review
  • 3 Proposed Method
  • 3.1 LP Detection and Classification
  • 3.2 Character Segmentation and Recognition
  • 4 Result and Discussion
  • 4.1 DLP Dataset
  • 4.2 Detection and Classification Results
  • 4.3 Character Recognition Results
  • 4.4 Real-Time Implementation Results
  • 5 Conclusion
  • References
  • Pre-trained Convolutional Neural Networks for Gender Classification
  • 1 Introduction
  • 2 Related Work
  • 3 Methodology
  • 3.1 Keras Models
  • 3.2 Custom CNN
  • 4 Results and Discussion
  • 5 Conclusion
  • References
  • AVAO Enabled Deep Learning Based Person Authentication Using Fingerprint
  • 1 Introduction
  • 2 Motivation.
  • 2.1 Literature Review.

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