DenseHillNet: a lightweight CNN for accurate classification of natural images.
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| Title: | DenseHillNet: a lightweight CNN for accurate classification of natural images. |
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| Authors: | Saqib, Sheikh Muhammad1, Zubair Asghar, Muhammad1, Iqbal, Muhammad1, Al-Rasheed, Amal2, Amir Khan, Muhammad3, amirkhan@uitm.edu.my, Ghadi, Yazeed4, Mazhar, Tehseen5, tehseenmazhar719@gmail.com |
| Source: | PeerJ Computer Science; Apr2024, p1-21, 21p |
| Database: | Applied Science & Technology Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 177325820 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=177325820 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.7717/peerj-cs.1995 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 1 Titles: – TitleFull: DenseHillNet: a lightweight CNN for accurate classification of natural images. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Saqib, Sheikh Muhammad – PersonEntity: Name: NameFull: Zubair Asghar, Muhammad – PersonEntity: Name: NameFull: Iqbal, Muhammad – PersonEntity: Name: NameFull: Al-Rasheed, Amal – PersonEntity: Name: NameFull: Amir Khan, Muhammad – PersonEntity: Name: NameFull: Ghadi, Yazeed – PersonEntity: Name: NameFull: Mazhar, Tehseen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 23765992 Titles: – TitleFull: PeerJ Computer Science Type: main |
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