Proceedings of International Conference on Frontiers in Computing and Systems [electronic resource] : COMSYS 2022 / Ram Sarkar, Sujata Pal, Subhadip Basu, Dariusz Plewczynski, Debotosh Bhattacharjee, editors.

Intro
Preface
Contents
About the Editors
Machine Learning and Applications
AVENet:Attention-Based VGG 16 with ELM for Obscene Image Classification
1 Introduction
2 Proposed Methodology
2.1 Dataset
2.2 Attention-Based VGG with ELM Classifier (AVENet)
2.3 Result Analysis
3 Conclusion
References
Analyzing Market Dynamics of Agricultural Commodities: A Case Study Based on Cotton
1 Introduction
2 Related Work
3 Dataset
4 Results
5 Conclusion
References

Feature Selection for Nepali Part-of-Speech Tagging in a Conditional Random Fields-Based System
1 Introduction
2 Literature Review
3 Our Approach for Nepali POS Tagging
3.1 Features of POS Tagging
4 Experiment
4.1 Baseline Model: Without Feature
4.2 CRF-A Model: Incorporation of Contextual Information
4.3 CRF-B: Incorporation of Affix Features
4.4 CRF-C: Incorporation of Lexical Features
4.5 Corpus Statistics
4.6 Results
4.7 Error Analysis and Observations
5 Conclusion
References

Design and Development of a ML-Based Safety-Critical Fire Detection System
1 Introduction
2 Related Work
3 Proposed Fire Detection System
3.1 Methodology
3.2 Experimental Setup
3.3 Alert System
3.4 Results
4 Conclusion and Future Work
References
Compressed Image Super-Resolution Using Pre-trained Model Assistance
1 Introduction
2 Related Work
3 Proposed Model
4 Experiment and Results
4.1 Implementation Overview
4.2 Results
4.3 Discussion
5 Conclusion
References

6 Optimization of Character Classes in Devanagari Ancient Manuscripts and Dataset Generation
Abstract
1 Introduction
2 Identification of Dataset-A
3 Identification of Dataset-B
4 Generation of Dataset
5 Experimental Setup
5.1 Feature Extraction
5.2 Classification
5.3 Experimental Results
5.4 Comparison with Existing Work
6 Conclusion
References
Deep Learning-Based Classification of Rice Varieties from Seed Coat Images
1 Introduction
2 Preliminaries
2.1 Dataset Description
3 Proposed Technique
3.1 Image Acquisition
3.2 Preprocessing

3.3 Model Development
3.4 Convolution Layer
3.5 Recurrent Layer
4 Experimental Results
4.1 Experimental Setup
4.2 Results and Visualizations
4.3 Performance Metrics
4.4 Training Curves
5 Conclusion
References
Leaf-Based Plant Disease Detection Using Intelligent Techniques-A Comprehensive Survey
1 Introduction
2 Literature Review
2.1 Detection of Plant Diseases with Segmentation
2.2 Detection of Plant Diseases Through Analysis of Color and Texture
2.3 Plant Disease Detection and Classification Using Artificial Intelligence and Machine Learning