Systematic Analysis of Deep Learning Models vs. Machine Learning

Dr. Sheshang Degadwala; Dhairya Vyas

doi:10.32628/CSEIT24104108

Authors

Dr. Sheshang Degadwala Professor / HOD, Department of Computer Engineering, Sigma University, Vadodara, Gujarat, India Author
Dhairya Vyas Managing Director, Shree Drashti Infotech LLP, Vadodara, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT24104108

Keywords:

Artificial Intelligence, Deep Learning, Machine Learning, Neural Networks, Feature Extraction, Hybrid Models

Abstract

Deep learning (DL) and classical machine learning (ML) models are compared and contrasted in this study, which offers a complete overview of the differences and technological improvements between the two types of models. Through an analysis of a diverse range of research publications, the study draws attention to the distinct advantages and uses of both techniques. Deep learning, which is characterized by its use of neural networks with several layers, is particularly effective at managing massive datasets that are not organized. It has also made great progress in the areas of image and audio recognition, natural language processing, and complicated pattern identification exercises. On the other hand, classic machine learning models, which are based on the extraction of features and simpler methods, continue to be quite successful in structured data situations such as classification, regression, and clustering challenges. By concentrating on aspects such as data quantity, computing resources, and unique application needs, the survey sheds light on the parameters that should be considered when selecting between deep learning and machine learning. In addition to this, it addresses the ever-changing environment of hybrid models, which combine methods from both deep learning and machine learning in order to capitalize on the advantages of both approaches. This study highlights the significance of contextual awareness in the fast-developing area of artificial intelligence by providing researchers and practitioners with useful insights that can be used to deploy the AI models that are the most appropriate for their particular requirements.

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References

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S. Degadwala, D. Vyas, K. N. Patel, M. Soni, P. Parkash Singh, and R. Maranan, “Optimizing Hindi Paragraph Summarization through PageRank Method,” in Proceedings of the 2nd International Conference on Edge Computing and Applications, ICECAA 2023, 2023, pp. 504–509. doi: 10.1109/ICECAA58104.2023.10212107. DOI: https://doi.org/10.1109/ICECAA58104.2023.10212107

S. Degadwala, D. Vyas, A. R. Raval, and M. Soni, “Crime Pattern Analysis and Prediction Using Regression Models,” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, pp. 771–776, 2023, doi: 10.1109/ICSSAS57918.2023.10331747. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331747

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D. D. Pandya, A. K. Patel, J. M. Purohit, M. N. Bhuptani, S. Degadwala, and D. Vyas, “Forecasting Number of Indian Startups using Supervised Learning Regression Models,” in 6th International Conference on Inventive Computation Technologies, ICICT 2023 - Proceedings, 2023, pp. 948–952. doi: 10.1109/ICICT57646.2023.10134480. DOI: https://doi.org/10.1109/ICICT57646.2023.10134480

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F. Patel, S. Mewada, S. Degadwala, and D. Vyas, “Exploring Transfer Learning Models for Multi-Class Classification of Infected Date Palm Leaves,” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, pp. 307–312, 2023, doi: 10.1109/ICSSAS57918.2023.10331746. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331746

D. Rathod, K. Patel, A. J. Goswami, S. Degadwala, and D. Vyas, “Exploring Drug Sentiment Analysis with Machine Learning Techniques,” in 6th International Conference on Inventive Computation Technologies, ICICT 2023 - Proceedings, 2023, pp. 9–12. doi: 10.1109/ICICT57646.2023.10134055. DOI: https://doi.org/10.1109/ICICT57646.2023.10134055

P. Bam, S. Degadwala, R. Upadhyay, and D. Vyas, “Spoken Language Recognization Based on Features and Classification Methods: A Review,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 868–873. doi: 10.1109/ICAIS53314.2022.9743090. DOI: https://doi.org/10.1109/ICAIS53314.2022.9743090

R. Baria, S. Degadwala, R. Upadhyay, and D. Vyas, “Theoretical Evaluation of Machine And Deep Learning For Detecting Fake News,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 325–329. doi: 10.1109/ICAIS53314.2022.9742864. DOI: https://doi.org/10.1109/ICAIS53314.2022.9742864

S. Dave, S. Degadwala, and D. Vyas, “DDoS Detection at Fog Layer in Internet of Things,” in International Conference on Edge Computing and Applications, ICECAA 2022 - Proceedings, 2022, pp. 610–617. doi: 10.1109/ICECAA55415.2022.9936524. DOI: https://doi.org/10.1109/ICECAA55415.2022.9936524

V. B. Gadhavi, S. Degadwala, and D. Vyas, “Transfer Learning Approach For Recognizing Natural Disasters Video,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 793–798. doi: 10.1109/ICAIS53314.2022.9743035. DOI: https://doi.org/10.1109/ICAIS53314.2022.9743035

H. Gupta, D. Patel, A. Makade, K. Gupta, O. P. Vyas, and A. Puliafito, “Risk Prediction in the Life Insurance Industry Using Federated Learning Approach,” in MELECON 2022 - IEEE Mediterranean Electrotechnical Conference, Proceedings, 2022, pp. 948–953. doi: 10.1109/MELECON53508.2022.9842869. DOI: https://doi.org/10.1109/MELECON53508.2022.9842869

J. Mahale, S. Degadwala, and D. Vyas, “Crop Prediction System based on Soil and Weather Characteristics,” in 6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022 - Proceedings, 2022, pp. 340–345. doi: 10.1109/I-SMAC55078.2022.9987366. DOI: https://doi.org/10.1109/I-SMAC55078.2022.9987366

D. D. Pandya, A. Jadeja, S. Degadwala, and D. Vyas, “Ensemble Learning based Enzyme Family Classification using n-gram Feature,” in Proceedings - 2022 6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022, 2022, pp. 1386–1392. doi: 10.1109/ICICCS53718.2022.9788292. DOI: https://doi.org/10.1109/ICICCS53718.2022.9788292

D. D. Pandya, G. Amarawat, A. Jadeja, S. Degadwala, and D. Vyas, “Analysis and Prediction of Location based Criminal Behaviors Through Machine Learning,” in International Conference on Edge Computing and Applications, ICECAA 2022 - Proceedings, 2022, pp. 1324–1332. doi: 10.1109/ICECAA55415.2022.9936498. DOI: https://doi.org/10.1109/ICECAA55415.2022.9936498

D. D. Pandya, N. S. Gupta, A. Jadeja, R. D. Patel, S. Degadwala, and D. Vyas, “Bias Protected Attributes Data Balancing using Map Reduce,” in 6th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2022 - Proceedings, 2022, pp. 1540–1544. doi: 10.1109/ICECA55336.2022.10009363. DOI: https://doi.org/10.1109/ICECA55336.2022.10009363

A. Patel, S. Degadwala, and D. Vyas, “Lung Respiratory Audio Prediction using Transfer Learning Models,” in 6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022 - Proceedings, 2022, pp. 1107–1114. doi: 10.1109/I-SMAC55078.2022.9986498. DOI: https://doi.org/10.1109/I-SMAC55078.2022.9986498

M. Shah, S. Degadwala, and D. Vyas, “Diet Recommendation System based on Different Machine Learners: A Review,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 290–295. doi: 10.1109/ICAIS53314.2022.9742919. DOI: https://doi.org/10.1109/ICAIS53314.2022.9742919

V. K. Singh, S. Pandey, S. Degadwala, and D. Vyas, “DNA and KAMLA Approaches in Metamorphic Cryptography: An Evaluation,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 1173–1178. doi: 10.1109/ICAIS53314.2022.9742764. DOI: https://doi.org/10.1109/ICAIS53314.2022.9742764

B. Trivedi, S. Degadwala, and D. Vyas, “Parallel Data Stream Anonymization Methods: A Review,” in Proceedings of the 2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 2022, pp. 887–891. doi: 10.1109/ICAIS53314.2022.9743084. DOI: https://doi.org/10.1109/ICAIS53314.2022.9743084

H. Dave, V. Patel, J. N. Mehta, S. Degadwala, and D. Vyas, “Regional Kidney Stone Detection and Classification in Ultrasound Images,” in Proceedings of the 3rd International Conference on Inventive Research in Computing Applications, ICIRCA 2021, 2021, pp. 1108–1112. doi: 10.1109/ICIRCA51532.2021.9545031. DOI: https://doi.org/10.1109/ICIRCA51532.2021.9545031

S. Degadwala, U. Chakraborty, P. Kuri, H. Biswas, A. N. Ali, and D. Vyas, “Real-Time Panorama and Image Stitching with Surf-Sift Features,” in Proceedings of the 6th International Conference on Inventive Computation Technologies, ICICT 2021, 2021, pp. 1111–1115. doi: 10.1109/ICICT50816.2021.9358586. DOI: https://doi.org/10.1109/ICICT50816.2021.9358586

S. Degadwala, S. A. Musa, D. Vyas, and P. Mitra, “IoT Defence: An Internet Based Remote Area Monitoring and Control System,” in Proceedings of the 5th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2021, 2021, pp. 487–491. doi: 10.1109/ICECA52323.2021.9676144. DOI: https://doi.org/10.1109/ICECA52323.2021.9676144

S. Degadwala, B. Patel, and D. Vyas, “A Review on Indian State/City Covid-19 Cases Outbreak Forecast utilizing Machine Learning Models,” in Proceedings of the 6th International Conference on Inventive Computation Technologies, ICICT 2021, 2021, pp. 1001–1005. doi: 10.1109/ICICT50816.2021.9358506. DOI: https://doi.org/10.1109/ICICT50816.2021.9358506

S. Degadwala, D. Vyas, H. Biswas, U. Chakraborty, and S. Saha, “Image Captioning Using Inception V3 Transfer Learning Model,” in Proceedings of the 6th International Conference on Communication and Electronics Systems, ICCES 2021, 2021, pp. 1103–1108. doi: 10.1109/ICCES51350.2021.9489111. DOI: https://doi.org/10.1109/ICCES51350.2021.9489111

S. Degadwala, D. Vyas, U. Chakraborty, H. Biswas, and A. R. Dider, “Moving Object Inpainting using Deep Learning,” in Proceedings of the 5th International Conference on Trends in Electronics and Informatics, ICOEI 2021, 2021, pp. 1701–1704. doi: 10.1109/ICOEI51242.2021.9452894. DOI: https://doi.org/10.1109/ICOEI51242.2021.9452894

S. Degadwala, D. Vyas, U. Chakraborty, A. R. Dider, and H. Biswas, “Yolo-v4 Deep Learning Model for Medical Face Mask Detection,” in Proceedings - International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021, 2021, pp. 209–213. doi: 10.1109/ICAIS50930.2021.9395857. DOI: https://doi.org/10.1109/ICAIS50930.2021.9395857

S. Degadwala, D. Vyas, and H. Dave, “Classification of COVID-19 cases using Fine-Tune Convolution Neural Network (FT-CNN),” in Proceedings - International Conference on Artificial Intelligence and Smart Systems, ICAIS 2021, 2021, pp. 609–613. doi: 10.1109/ICAIS50930.2021.9395864. DOI: https://doi.org/10.1109/ICAIS50930.2021.9395864

S. Degadwala, D. Vyas, M. R. Hossain, A. R. DIder, M. N. Ali, and P. Kuri, “Location-Based Modelling and Analysis of Threats by Using Text Mining,” in Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021, 2021, pp. 1940–1944. doi: 10.1109/ICESC51422.2021.9532825. DOI: https://doi.org/10.1109/ICESC51422.2021.9532825

S. Patel, H. Patel, D. Vyas, and S. Degadwala, “Multi-Classifier Analysis of Leukemia Gene Expression from Curated Microarray Database (CuMiDa),” in Proceedings - 2nd International Conference on Smart Electronics and Communication, ICOSEC 2021, 2021, pp. 1174–1178. doi: 10.1109/ICOSEC51865.2021.9591854. DOI: https://doi.org/10.1109/ICOSEC51865.2021.9591854

S. Degadwala, U. Chakraborty, S. Saha, H. Biswas, and D. Vyas, “EPNet: Efficient patch-based deep network for real-time semantic segmentation,” in Proceedings of the 3rd International Conference on Intelligent Sustainable Systems, ICISS 2020, 2020, pp. 611–615. doi: 10.1109/ICISS49785.2020.9316079. DOI: https://doi.org/10.1109/ICISS49785.2020.9316079

S. Degadwala, D. Vyas, H. Dave, and A. Mahajan, “Visual Social Distance Alert System Using Computer Vision Deep Learning,” in Proceedings of the 4th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2020, 2020, pp. 1512–1516. doi: 10.1109/ICECA49313.2020.9297510. DOI: https://doi.org/10.1109/ICECA49313.2020.9297510