Affiliation:
1. SGGS IE&T, Nanded, India
Abstract
With the advances in the computer science field, various new data science techniques have been emerged. Convolutional Neural Network (CNN) is one of the Deep Learning techniques which have captured lots of attention as far as real world applications are considered. It is nothing but the multilayer architecture with hidden computational power which detects features itself. It doesn't require any handcrafted features. The remarkable increase in the computational power of Convolutional Neural Network is due to the use of Graphics processor units, parallel computing, also the availability of large amount of data in various variety forms. This paper gives the broad view of various supervised Convolutional Neural Network applications with its salient features in the fields, mainly Computer vision for Pattern and Object Detection, Natural Language Processing, Speech Recognition, Medical image analysis.
Cited by
21 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Classifying Philippine Medicinal Plants Based on Their Leaves Using Deep Learning;2023 IEEE World AI IoT Congress (AIIoT);2023-06-07
2. CX-R Classification Using DCNN Method;2023 2nd International Conference for Innovation in Technology (INOCON);2023-03-03
3. Covid19 Disease Assessment Using CNN Architecture;2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM);2023-02-22
4. Automatic Recognition and Categorization of Tomato Leaf Syndrome of Diseases Using Deep Learning Algorithms;Information and Communication Technology for Competitive Strategies (ICTCS 2022);2023
5. An Efficient COVID-19-Based Disease Detection on X-Ray Images Using CNN Model;ICT Infrastructure and Computing;2023