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Sabha, Ambreen. SAPS : automatic saffron adulteration prediction systems, research issues, and prospective solutions. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2021.
SAPS : automatic saffron adulteration prediction systems, research issues, and prospective solutions
Name: Amin, Junaid
Organization :
Central University of Jammu. Dept. of Computer Science and IT
Email :
mohdjunaidkashmeer@gmail.com
Name: Selwal, Arvind
Organization :
Central University of Jammu. Dept. of Computer Science and IT
Email :
arvind.csit@cujammu.ac.in
Name: Sabha, Ambreen
Organization :
Central University of Jammu. Dept. of Computer Science and IT
Email :
ambreensabha45@gmail.com
LCSH:
Saffron crocus
-- Analysis
LCSH:
Food
-- Quality control
Abstract:
Saffron is one of the costlier spices that is cultivated
in specific regions of the world. Due to its limited availability
and higher demand in the population, thus saffron adulteration is
one of the crucial challenges. It becomes very difficult for
human vision to discriminate between real and adulterated
saffron samples. With the emergence of visual computing and
machine learning algorithms, automatic saffron adulteration
prediction becomes an easier task. In this paper, we expound the
state of the art of intelligent saffron adulteration predication
systems along with various research issues and future
perspectives. The present study is an attempt to explore the
existing methods of handcrafted features to train linear
classifiers such as artificial neural networks (ANN), support
vector machine (SVM), and decision tree (DT). However, the
majority of the techniques exhibit promising performance but
the problem of generalization capabilities (unseen samples)
and scarcity of the saffron databases are the open research
challenges. Moreover, deep neural networks are the viable
solution for designing an efficient and robust saffron
adulteration prediction system (SAPS).
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2021
Modified:
2024-06-11
Issued:
2024-05-31
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Computer Society. 2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT 2021) (pp.64-71). Los Alamitos, CA : IEEE Computer Society
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
ใช้เวลา
0.03506 วินาที
Amin, Junaid
| Title | Contributor | Type |
|---|---|---|
| SAPS : automatic saffron adulteration prediction systems, research issues, and prospective solutions
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Amin, Junaid;Selwal, Arvind;Sabha, Ambreen | บทความ/Article |
Selwal, Arvind
| Title | Contributor | Type |
|---|---|---|
| Computational intelligence paradigms for audio-based video summarization
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kalsi, Akhil;Selwal, Arvind;Sabha, Ambreen | บทความ/Article | |
| Fingerprint spoofing attacks and their deep learning-enabled remediation : state-of-the-art, taxonomy, and future directions
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Ishfaq, Rutbaa;Selwal, Arvind;Sharma, Deepika | บทความ/Article | |
| SAPS : automatic saffron adulteration prediction systems, research issues, and prospective solutions
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Amin, Junaid;Selwal, Arvind;Sabha, Ambreen | บทความ/Article | |
| FinCaT : fingerprint cancellable template protection remediation schemes, challenges, and future directions
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Sehar, Eain Ul;Selwal, Arvind;Sharma, Deepika | บทความ/Article |
Sabha, Ambreen
| Title | Contributor | Type |
|---|---|---|
| Computational intelligence paradigms for audio-based video summarization
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kalsi, Akhil;Selwal, Arvind;Sabha, Ambreen | บทความ/Article | |
| SAPS : automatic saffron adulteration prediction systems, research issues, and prospective solutions
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Amin, Junaid;Selwal, Arvind;Sabha, Ambreen | บทความ/Article |