A Review on Skin Melanoma Classification using different ML and DL Models
DOI:
https://doi.org/10.32628/CSEIT24103124Keywords:
Skin Melanoma, Machine Learning, Deep Learning, Classification Models, Diagnostic AccuracyAbstract
This review explores the classification of skin melanoma utilizing various machine learning (ML) and deep learning (DL) models, highlighting the advancements and comparative performance of these methodologies. Skin melanoma, a serious type of skin cancer, demands early and accurate diagnosis for effective treatment. The review covers a range of ML techniques such as support vector machines, decision trees, and ensemble methods, alongside \DL approaches including convolutional neural networks and recurrent neural networks. Emphasis is placed on the models' accuracy, computational efficiency, and the datasets used for training and validation. The review underscores the potential of DL models to outperform traditional ML methods due to their ability to automatically extract and learn intricate features from large datasets, thus offering promising prospects for enhanced diagnostic precision in melanoma classification.
Downloads
References
V. D. Midasala, B. Prabhakar, J. Krishna Chaitanya, K. Sirnivas, D. Eshwar, and P. M. Kumar, “MFEUsLNet: Skin cancer detection and classification using integrated AI with multilevel feature extraction-based unsupervised learning,” Engineering Science and Technology, an International Journal, vol. 51, no. February, p. 101632, 2024, doi: 10.1016/j.jestch.2024.101632. DOI: https://doi.org/10.1016/j.jestch.2024.101632
A. Naeem and T. Anees, “DVFNet: A deep feature fusion-based model for the multiclassification of skin cancer utilizing dermoscopy images,” PLoS ONE, vol. 19, no. 3 March, pp. 1–27, 2024, doi: 10.1371/journal.pone.0297667. DOI: https://doi.org/10.1371/journal.pone.0297667
N. A. AlSadhan, S. A. Alamri, M. M. Ben Ismail, and O. Bchir, “Skin Cancer Recognition Using Unified Deep Convolutional Neural Networks,” Cancers, vol. 16, no. 7, 2024, doi: 10.3390/cancers16071246. DOI: https://doi.org/10.3390/cancers16071246
T. Imran, A. S. Alghamdi, and M. S. Alkatheiri, “Enhanced Skin Cancer Classification using Deep Learning and Nature-based Feature Optimization,” Engineering, Technology and Applied Science Research, vol. 14, no. 1, pp. 12702–12710, 2024, doi: 10.48084/etasr.6604. DOI: https://doi.org/10.48084/etasr.6604
G. M. S. Himel, M. M. Islam, K. A. Al-Aff, S. I. Karim, and M. K. U. Sikder, “Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System,” International Journal of Biomedical Imaging, vol. 2024, 2024, doi: 10.1155/2024/3022192. DOI: https://doi.org/10.1155/2024/3022192
K. Mridha, M. M. Uddin, J. Shin, S. Khadka, and M. F. Mridha, “An Interpretable Skin Cancer Classification Using Optimized Convolutional Neural Network for a Smart Healthcare System,” IEEE Access, vol. 11, no. March, pp. 41003–41018, 2023, doi: 10.1109/ACCESS.2023.3269694. DOI: https://doi.org/10.1109/ACCESS.2023.3269694
J. S M, M. P, C. Aravindan, and R. Appavu, “Classification of skin cancer from dermoscopic images using deep neural network architectures,” Multimedia Tools and Applications, vol. 82, no. 10, pp. 15763–15778, 2023, doi: 10.1007/s11042-022-13847-3. DOI: https://doi.org/10.1007/s11042-022-13847-3
H. L. Gururaj, N. Manju, A. Nagarjun, V. N. Manjunath Aradhya, and F. Flammini, “DeepSkin: A Deep Learning Approach for Skin Cancer Classification,” IEEE Access, vol. 11, no. May, pp. 50205–50214, 2023, doi: 10.1109/ACCESS.2023.3274848. DOI: https://doi.org/10.1109/ACCESS.2023.3274848
G. Yang, S. Luo, and P. Greer, “A Novel Vision Transformer Model for Skin Cancer Classification,” Neural Processing Letters, 2023, doi: 10.1007/s11063-023-11204-5. DOI: https://doi.org/10.1007/s11063-023-11204-5
Y. S. Alsahafi, M. A. Kassem, and K. M. Hosny, “Skin-Net: a novel deep residual network for skin lesions classification using multilevel feature extraction and cross-channel correlation with detection of outlier,” Journal of Big Data, vol. 10, no. 1, 2023, doi: 10.1186/s40537-023-00769-6. DOI: https://doi.org/10.1186/s40537-023-00769-6
A. Al-Rasheed, A. Ksibi, M. Ayadi, A. I. A. Alzahrani, M. Zakariah, and N. Ali Hakami, “An Ensemble of Transfer Learning Models for the Prediction of Skin Cancers with Conditional Generative Adversarial Networks,” Diagnostics, vol. 12, no. 12, 2022, doi: 10.3390/diagnostics12123145. DOI: https://doi.org/10.3390/diagnostics12123145
N. Ahmad et al., “A novel framework of multiclass skin lesion recognition from dermoscopic images using deep learning and explainable AI,” Frontiers in Oncology, vol. 13, no. June, pp. 1–17, 2023, doi: 10.3389/fonc.2023.1151257. DOI: https://doi.org/10.3389/fonc.2023.1151257
M. A. Arshed, S. Mumtaz, M. Ibrahim, S. Ahmed, M. Tahir, and M. Shafi, “Multi-Class Skin Cancer Classification Using Vision Transformer Networks and Convolutional Neural Network-Based Pre-Trained Models,” Information (Switzerland), vol. 14, no. 7, 2023, doi: 10.3390/info14070415. DOI: https://doi.org/10.3390/info14070415
G. Wang, P. Yan, Q. Tang, L. Yang, and J. Chen, “Multiscale Feature Fusion for Skin Lesion Classification,” BioMed Research International, vol. 2023, 2023, doi: 10.1155/2023/5146543. DOI: https://doi.org/10.1155/2023/5146543
S. S. Noronha, M. A. Mehta, D. Garg, K. Kotecha, and A. Abraham, “Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions,” IEEE Access, vol. 11, no. November, pp. 140348–140381, 2023, doi: 10.1109/ACCESS.2023.3339635. DOI: https://doi.org/10.1109/ACCESS.2023.3339635
S. Degadwala, D. Vyas, and M. Soni, “Unveiling Cholera Patterns through Machine Learning Regression for Precise Forecasting,” Proceedings - 2024 5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024, pp. 39–44, 2024, doi: 10.1109/ICMCSI61536.2024.00012. DOI: https://doi.org/10.1109/ICMCSI61536.2024.00012
D. D. Pandya, A. Jadeja, S. Degadwala, and D. Vyas, “Diagnostic Criteria for Depression based on Both Static and Dynamic Visual Features,” in IDCIoT 2023 - International Conference on Intelligent Data Communication Technologies and Internet of Things, Proceedings, 2023, pp. 635–639. doi: 10.1109/IDCIoT56793.2023.10053450. DOI: https://doi.org/10.1109/IDCIoT56793.2023.10053450
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
V. Desai, S. Degadwala, and D. Vyas, “Multi-Categories Vehicle Detection For Urban Traffic Management,” in Proceedings of the 2023 2nd International Conference on Electronics and Renewable Systems, ICEARS 2023, 2023, pp. 1486–1490. doi: 10.1109/ICEARS56392.2023.10085376. DOI: https://doi.org/10.1109/ICEARS56392.2023.10085376
C. H. Patel, D. Undaviya, H. Dave, S. Degadwala, and D. Vyas, “EfficientNetB0 for Brain Stroke Classification on Computed Tomography Scan,” in Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023, 2023, pp. 713–718. doi: 10.1109/ICAAIC56838.2023.10141195. DOI: https://doi.org/10.1109/ICAAIC56838.2023.10141195
V. N. Dasavandi Krishnamurthy, S. Degadwala, and D. Vyas, “Forecasting Future Sea Level Rise: A Data-driven Approach using Climate Analysis,” Proceedings of the 2nd International Conference on Edge Computing and Applications, ICECAA 2023, pp. 646–651, 2023, doi: 10.1109/ICECAA58104.2023.10212399. DOI: https://doi.org/10.1109/ICECAA58104.2023.10212399
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
S. Degadwala, S. S. Dave, D. Vyas, N. A. Patel, V. I. Gohil, and K. Rana, “Enhancing Mesothelioma Cancer Diagnosis through Ensemble Learning Techniques,” 3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, pp. 628–632, 2023, doi: 10.1109/ICIMIA60377.2023.10425887. DOI: https://doi.org/10.1109/ICIMIA60377.2023.10425887
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
S. Degadwala, D. Vyas, S. Panesar, D. Ebenezer, D. D. Pandya, and V. D. Shah, “Revolutionizing Hops Plant Disease Classification: Harnessing the Power of Transfer Learning,” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, pp. 1706–1711, 2023, doi: 10.1109/ICSCNA58489.2023.10370692. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370692
S. Mewada, F. Patel, S. Degadwala, and D. Vyas, “Enhancing Raga Identification in Indian Classical Music with FCN-based Models,” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, pp. 980–985, 2023, doi: 10.1109/ICSCNA58489.2023.10370046. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370046
F. Ahamad, D. K. Lobiyal, S. Degadwala, and D. Vyas, “Inspecting and Finding Faults in Railway Tracks using Wireless Sensor Networks,” in 6th International Conference on Inventive Computation Technologies, ICICT 2023 - Proceedings, 2023, pp. 1241–1245. doi: 10.1109/ICICT57646.2023.10134164. DOI: https://doi.org/10.1109/ICICT57646.2023.10134164
S. Degadwala, D. Vyas, S. Upadhyay, R. Upadhyay, and H. S. Patel, “Determine the Degree of Malignancy in Breast Cancer using Machine Learning,” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, pp. 483–487, 2023, doi: 10.1109/I-SMAC58438.2023.10290430. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290430
S. Degadwala, D. Vyas, A. Jadeja, and D. D. Pandya, “Enhancing Alzheimer Stage Classification of MRI Images through Transfer Learning,” in Proceedings of the 5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023, 2023, pp. 733–737. doi: 10.1109/ICIRCA57980.2023.10220651. DOI: https://doi.org/10.1109/ICIRCA57980.2023.10220651
S. Degadwala, D. Vyas, A. Jadeja, and D. D. Pandya, “Empowering Maxillofacial Diagnosis Through Transfer Learning Models,” in Proceedings of the 5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023, 2023, pp. 728–732. doi: 10.1109/ICIRCA57980.2023.10220830. DOI: https://doi.org/10.1109/ICIRCA57980.2023.10220830
J. N. Mehta, H. Lakhani, H. Dave, S. Degadwala, and D. Vyas, “EEG Brainwave Data Classification of a Confused Student Using Moving Average Feature,” Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, pp. 1461–1466, 2023, doi: 10.1109/ICPCSN58827.2023.00243. DOI: https://doi.org/10.1109/ICPCSN58827.2023.00243
S. Degadwala, R. Upadhyay, S. Upadhyay, M. Soni, D. J. Parikh, and D. Vyas, “DeepTread: Exploring Transfer Learning in Tyre Quality Classification,” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, pp. 1448–1453, 2023, doi: 10.1109/ICSCNA58489.2023.10370168. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370168
S. Degadwala, D. Vyas, S. Trivedi, H. Dave, P. K. Nilaykumar, and P. Dalal, “Revolutionizing Prostate Cancer Diagnosis: Harnessing the Potential of Transfer Learning for MRI-Based Classification,” Proceedings of the 4th International Conference on Smart Electronics and Communication, ICOSEC 2023, pp. 938–943, 2023, doi: 10.1109/ICOSEC58147.2023.10275879. DOI: https://doi.org/10.1109/ICOSEC58147.2023.10275879
S. Degadwala, R. Upadhyay, S. Upadhyay, S. S. Dave, D. Mahida, and D. Vyas, “Enhancing Fleet Management with ESP8266-based IoT Sensors for Weight and Location Tracking,” 3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, pp. 13–17, 2023, doi: 10.1109/ICIMIA60377.2023.10425949. DOI: https://doi.org/10.1109/ICIMIA60377.2023.10425949
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
S. Mewada, F. Patel, S. Degadwala, and D. Vyas, “Improved CAD Classification with Ensemble Classifier and Attribute Elimination,” in Proceedings - 2023 3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023, 2023, pp. 238–243. doi: 10.1109/ICUIS60567.2023.00048. DOI: https://doi.org/10.1109/ICUIS60567.2023.00048
D. D. Pandya, S. K. Patel, A. H. Qureshi, A. J. Goswami, S. Degadwala, and D. Vyas, “Multi-Class Classification of Vector Borne Diseases using Convolution Neural Network,” in Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023, 2023, pp. 1638–1645. doi: 10.1109/ICAAIC56838.2023.10140654. DOI: https://doi.org/10.1109/ICAAIC56838.2023.10140654
D. D. Pandya, P. A. Patel, H. H. Patel, A. J. Goswami, S. Degadwala, and D. Vyas, “Unveiling the Power of Collective Intelligence: A Voting-based Approach for Dementia Classification,” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, pp. 478–482, 2023, doi: 10.1109/I-SMAC58438.2023.10290165. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290165
S. Degadwala, D. Vyas, A. Jadeja, and D. D. Pandya, “Enhancing Prostate Cancer Diagnosis: Leveraging XGBoost for Accurate Classification,” Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023, pp. 1776–1781, 2023, doi: 10.1109/ICAISS58487.2023.10250511. DOI: https://doi.org/10.1109/ICAISS58487.2023.10250511
S. Degadwala, D. Vyas, D. D. Pandya, and H. Dave, “Multi-Class Pneumonia Classification Using Transfer Deep Learning Methods,” in Proceedings of the 3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023, 2023, pp. 559–563. doi: 10.1109/ICAIS56108.2023.10073807. DOI: https://doi.org/10.1109/ICAIS56108.2023.10073807
D. D. Pandya, S. Degadwala, D. Vyas, S. V. Sureshbhai, L. Ainapurapu, and N. S. Bhavsar, “Advancing Erythemato-Squamous Disease Classification with Multi-class Machine Learning,” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, pp. 542–547, 2023, doi: 10.1109/I-SMAC58438.2023.10290599. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290599
D. D. Pandya, S. Degadwala, D. Vyas, V. N. Solanki, S. V. Sureshbhai, and H. G. Patel, “Advancements in Multiple Sclerosis Disease Classification Through Machine Learning,” in Proceedings - 2023 3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023, 2023, pp. 64–69. doi: 10.1109/ICUIS60567.2023.00019. DOI: https://doi.org/10.1109/ICUIS60567.2023.00019
A. Patel, S. Degadwala, and D. Vyas, “Enhancing Traffic Management with YOLOv5-Based Ambulance Tracking System,” Canadian Conference on Electrical and Computer Engineering, vol. 2023-September, pp. 528–532, 2023, doi: 10.1109/CCECE58730.2023.10288751. DOI: https://doi.org/10.1109/CCECE58730.2023.10288751
F. Patel, S. Mewada, S. Degadwala, and D. Vyas, “Recognition of Pistachio Species with Transfer Learning Models,” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, pp. 250–255, 2023, doi: 10.1109/ICSSAS57918.2023.10331907. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331907
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
H. Lakhani, D. Undaviya, H. Dave, S. Degadwala, and D. Vyas, “PET-MRI Sequence Fusion using Convolution Neural Network,” in 6th International Conference on Inventive Computation Technologies, ICICT 2023 - Proceedings, 2023, pp. 317–321. doi: 10.1109/ICICT57646.2023.10134462. DOI: https://doi.org/10.1109/ICICT57646.2023.10134462
S. Degadwala, D. Vyas, P. Mitra, S. S. E. Roja, and S. K. Mandal, “Methods of Transfer Learning for Multiclass Hair Disease Categorization,” in 2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023 - Proceedings, Dec. 2023, pp. 612–616. doi: 10.1109/ICACRS58579.2023.10404492. DOI: https://doi.org/10.1109/ICACRS58579.2023.10404492
S. Degadwala, D. Vyas, A. Kothari, and U. Khunt, “Cancer Death Cases Forecasting using Supervised Machine Learning,” in 2023 4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023 - Proceedings, 2023, pp. 903–907. doi: 10.1109/ICESC57686.2023.10193685. DOI: https://doi.org/10.1109/ICESC57686.2023.10193685
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
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
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
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
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
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
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
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
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
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
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. 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, 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, 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,” Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021, pp. 1940–1944, 2021, doi: 10.1109/ICESC51422.2021.9532825. DOI: https://doi.org/10.1109/ICESC51422.2021.9532825
Downloads
Published
Issue
Section
License
Copyright (c) 2024 International Journal of Scientific Research in Computer Science, Engineering and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
