Classification of Pandavas Figure in Shadow Puppet Images using Convolutional Neural Networks
نویسندگان
چکیده
Indonesia is a nation with various ethnicities and rich cultural backgrounds that span from Sabang to Merauke. One of the products Indonesian society shadow puppet. Shadow puppet has been internationally renowned as masterpiece art recognized by UNESCO. The development very dependent on technological sophistication it may shift existing traditional culture out memory nation. Practices modern life busy activities people exacerbate condition make ignore culture. This study seeks preserve making puppets object classification. We use deep learning algorithm called convolutional neural network (CNN) classify 430 images into 4 classes. proportion training, validation test data 70 20 10. experiments show most efficient model obtained 3 convolution layer. It reaches an accuracy rate 0.93 drop 0.2
منابع مشابه
Classification of Time-Series Images Using Deep Convolutional Neural Networks
Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifie...
متن کاملClassification of breast cancer histology images using Convolutional Neural Networks
Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods desig...
متن کاملClassification of Photo and Sketch Images Using Convolutional Neural Networks
In this study we propose a Convolutional Neural Network(CNN) which can classify hand drawn sketch images. Though CNN is known to be very effective on classification of realistic images, there are few studies on CNN dealing with nonphotorealistic images and even more images those types are mixing. Classifying non-photorealistic images is difficult mainly because there are no large datasets. In t...
متن کاملImage Classification using Convolutional Neural Networks
The specific paper I’ve chosen is titled “ImageNet Classification with Deep Convolutional Neural Networks” [1]. ImageNet is an annual competition in image recognition where researchers in the field pit their models against each other to achieve the highest classification accuracy on the same set of images. The model put forward in this paper, named AlexNet from it’s main author, beat the second...
متن کاملAcoustic Event Classification Using Convolutional Neural Networks
Acoustic scene classification (ASC) aims to distinguish between different acoustic environments and is a technology which can be used by smart devices for contextualization and personalization. Standard algorithms exploit hand-crafted features which are unlikely to offer the best potential for reliable classification. This paper reports the first application of convolutional neural networks (CN...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Khazanah informatika
سال: 2021
ISSN: ['2621-038X', '2477-698X']
DOI: https://doi.org/10.23917/khif.v7i1.12484