Sports Events Classification Using Convolutional Neural Networks

dc.contributor.authorShultana, Shahana
dc.contributor.authorMoharram, Md. Shakil
dc.date.accessioned2019-08-10T06:40:00Z
dc.date.available2019-08-10T06:40:00Z
dc.date.issued2018-11
dc.description.abstractAnalysis of different sports data to get valuable insight has become immensely important now-a-days. Profuse application of Artificial Intelligence in different sectors has become a very popular trend as well. However, application of AI in sports analytics is still a new research domain left for exploration. With a view to applying AI in sports analytics, we have deployed Inception V3 and MobileNet which are Google's most popular Convolutional Neural Networks to successfully recognize 5 different sports events from a huge image dataset of these events. We also developed a Convolutional Neural Network model which name is SP-Net and we trained our proposed model with these 5 different sports events. SP-Net correctly predicted the class almost all images during the period of testing and gives a high performance. In terms of performance our proposed model SP Net surpass Inception v3 and MobileNet both of these models. Besides, Inception v3 and MobileNet also achieved a very high performance in terms of accuracy, precision, recall and f-measure while applied on the target dataset for successful classification.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/3283
dc.identifier.urihttp://hdl.handle.net/123456789/3283
dc.language.isoen_US
dc.publisherDaffodil International University
dc.sourceDIU Institutional Repository
dc.subjectComputer Science
dc.subjectneural network
dc.subjectArtificial Intelligence
dc.titleSports Events Classification Using Convolutional Neural Networks
dc.typeOther

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
P12761 (10%).pdf.txt
Size:
41.68 KB
Format:
Adobe Portable Document Format

Collections