Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Hilman F. Pardede"'
Autor:
Arnetta Listiana Dewi, Hilman F. Pardede, Endang Suryawati, Hasih Pratiwi, Ana Heryana, Asri R Yuliani, Ade Ramdan
Publikováno v:
Jurnal Elektronika dan Telekomunikasi, Vol 24, Iss 1, Pp 25-30 (2024)
The implementation of object detection for autonomous vehicles is essential as it is necessary to identify common object on the street so proper response could be designed. While single stage object may be smaller in computations, two-stage object de
Externí odkaz:
https://doaj.org/article/5e1d44a543f64a619570bf2134f8b809
Publikováno v:
Jurnal Abdimas Prakasa Dakara, Vol 2, Iss 2, Pp 83-91 (2022)
Memahami kekuatan media harus dipromosikan pada semua tingkatan. Upaya pengembangan literasi media, baik dalam bentuk pemikiran maupun dalam melakukan kegiatan penyuluhan, perlu dilakukan dan didukung oleh berbagai pemangku kepentingan. Apalagi di er
Externí odkaz:
https://doaj.org/article/5f8e37ad096749c4ae0134a9656fa3f5
Autor:
Vicky Zilvan, Ade Ramdan, Ana Heryana, Dikdik Krisnandi, Endang Suryawati, R. Sandra Yuwana, R. Budiarianto S. Kusumo, Hilman F. Pardede
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 6, Pp 3332-3342 (2022)
It is common to have various clones from cross-seedlings or unintended planting by the farmers in a tea plantation. Since each tea clone has distinctive features such as quality, resistance to diseases, etc., visual inspections are usually conducted
Externí odkaz:
https://doaj.org/article/a442bfac9146424bbb8cceaaa07b10f0
Autor:
Endang Suryawati, Hilman F. Pardede, Vicky Zilvan, Ade Ramdan, Dikdik Krisnandi, Ana Heryana, R. Sandra Yuwana, R. Budiarianto Suryo Kusumo, Andria Arisal, Ahmad Afif Supianto
Publikováno v:
Journal of Big Data, Vol 8, Iss 1, Pp 1-17 (2021)
Abstract In this paper, we propose a novel deep learning-based feature learning architecture for object classification. Conventionally, deep learning methods are trained with supervised learning for object classification. But, this would require larg
Externí odkaz:
https://doaj.org/article/4f0f66f0b2214ca9ad9196086b4dbb23
Autor:
R. Sandra Yuwana, Fani Fauziah, Ana Heryana, Dikdik Krisnandi, R. Budiarianto Suryo Kusumo, Hilman F. Pardede
Publikováno v:
Jurnal Elektronika dan Telekomunikasi, Vol 20, Iss 1, Pp 29-35 (2020)
Deep learning technology has a better result when trained using an abundant amount of data. However, collecting such data is expensive and time consuming. On the other hand, limited data often be the inevitable condition. To increase the number of da
Externí odkaz:
https://doaj.org/article/0aa51d1b9a814a92be78659902893b91
Autor:
Hilman F. Pardede, Endang Suryawati, Vicky Zilvan, Ade Ramdan, R. Budiarianto S. Kusumo, Ana Heryana, R. Sandra Yuwana, Dikdik Krisnandi, Agus Subekti, Fani Fauziah, Vitria P. Rahadi
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-21 (2020)
Abstract At the moment, there are increasing trends of using deep learning for plant diseases detection. However, their implementations may be difficult in developing countries due to several reasons. First, existing deep learning models are usually
Externí odkaz:
https://doaj.org/article/354f295f8d28498fb6624b02ebeef5c7
Autor:
Ade Ramdan, Endang Suryawati, R. Budiarianto Suryo Kusumo, Hilman F. Pardede, Oka Mahendra, Rico Dahlan, Fani Fauziah, Heri Syahrian
Publikováno v:
Jurnal Elektronika dan Telekomunikasi, Vol 19, Iss 2, Pp 45-50 (2019)
One factor affecting the quality of tea is the selection of plant material that would be planted on the field. Clonal selection is a common way to produce tea with better quality. However, as a natural cross pollination species, tea often consists of
Externí odkaz:
https://doaj.org/article/137c0f26858a499db6346c87b997865f
Autor:
Dikdik Krisnandi, Hilman F. Pardede, R. Sandra Yuwana, Vicky Zilvan, Ana Heryana, Fani Fauziah, Vitria Puspitasari Rahadi
Publikováno v:
CommIT Journal, Vol 13, Iss 2, Pp 67─77-67─77 (2019)
Plant diseases can cause a significant decrease in tea crop production. Early disease detection can help to minimize the loss. For tea plants, experts can identify the diseases by visual inspection on the leaves. However, providing experts to deal wi
Externí odkaz:
https://doaj.org/article/7fbc2207f9ea4acebce725dde9402af1
Autor:
R. Budiarianto Suryo Kusumo, Ade Ramdan, Hilman F. Pardede, R. Sandra Yuwana, Dikdik Krisnandi, Vicky Zilvan, Endang Suryawati, Ana Heryana
Publikováno v:
Journal of King Saud University - Computer and Information Sciences. 34:3332-3342
It is common to have various clones from cross-seedlings or unintended planting by the farmers in a tea plantation. Since each tea clone has distinctive features such as quality, resistance to diseases, etc., visual inspections are usually conducted
Autor:
Zahra Cantiabela, Hilman F. Pardede, Vicky Zilvan, Winita Sulandari, Raden Sandra Yuwana, Ahmad Afif Supianto, Dikdik Krisnandi
Publikováno v:
Proceedings of the 2022 International Conference on Computer, Control, Informatics and Its Applications.