Sheep are livestock that ranks third after cows and goats that meet the needs of meat for the people of Indonesia, therefore it is very important to know the health condition of the sheep that will be consumed later. Sick sheep can be identified based on the sheep’s facial expressions. In this study the authors applied VGG19 to identify sick sheep face. System performance is measured based on the value of accuracy, precision, recall, and F-Measure. After testing starting from 50 epochs to 200 with a learning rate (0.0001), and trying various optimizers such as Adamax, SGD (Stochastic Gradient Descent), and Adam, the results show an accuracy value of 89.4% and an average precision of 65.6%, recall 81% and f-measure 69.7%, with an mcc value of 0.44 using epoch 100, learning rate 0.0001, and the Adamax optimizer. These values are influenced by the dataset of the training image of 800 images, the validation image of 229 images, and the test image of 144 images. In testing for search the best side of the sheep’s face image to be identified by the system, get the results that the sheep’s face image from the front side gets an accuracy value of 94% with an average precision of 49%, recall 48% and f-measure 48% with an mcc value. -0.03.
Skip Nav Destination
Article navigation
20 August 2024
INTERNATIONAL CONFERENCE ON GREEN TECHNOLOGY AND DESIGN (ICGTD) 2021: Human Behavior and Its Relevance in Technology and Design Research for Supporting the Recovery of Post-Pandemic Environment
2–3 December 2021
Bandung, Indonesia
Research Article|
August 20 2024
Identification the face image of the sick sheep using visual geometry group (VGG) 19
Yusup Miftahuddin;
Yusup Miftahuddin
a)
1
Institut Teknologi Nasional
, Jl. PH.H. Mustofa No.23 Bandung 40124, Indonesia
a)Corresponding author: [email protected]
Search for other works by this author on:
Muhammad Fathan Ar-Rabbani
Muhammad Fathan Ar-Rabbani
1
Institut Teknologi Nasional
, Jl. PH.H. Mustofa No.23 Bandung 40124, Indonesia
Search for other works by this author on:
a)Corresponding author: [email protected]
AIP Conf. Proc. 2744, 020008 (2024)
Citation
Yusup Miftahuddin, Muhammad Fathan Ar-Rabbani; Identification the face image of the sick sheep using visual geometry group (VGG) 19. AIP Conf. Proc. 20 August 2024; 2744 (1): 020008. https://doi.org/10.1063/5.0181709
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
15
Views
Citing articles via
Inkjet- and flextrail-printing of silicon polymer-based inks for local passivating contacts
Zohreh Kiaee, Andreas Lösel, et al.
Effect of coupling agent type on the self-cleaning and anti-reflective behaviour of advance nanocoating for PV panels application
Taha Tareq Mohammed, Hadia Kadhim Judran, et al.
Design of a 100 MW solar power plant on wetland in Bangladesh
Apu Kowsar, Sumon Chandra Debnath, et al.
Related Content
Time-series analysis for online recognition and localization of sick pig (Sus scrofa) cough sounds
J. Acoust. Soc. Am. (December 2008)
Transfer learning based VGG-16 model for detection of COVID-19 from chest X-ray images
AIP Conf. Proc. (August 2024)
Performance comparison of the convolutional neural network optimizer for photosynthetic pigments prediction on plant digital image
AIP Conf. Proc. (March 2019)