Cat Breeds Classification Using Compound Model Scaling Convolutional Neural Networks.

Karlita, Tita; Choirunisa, Nadia Azahro; Asmara, Rengga; Setyorini, Fitri

doi:10.2991/assehr.k.220301.150

Cited by 6 publications

(5 citation statements)

References 5 publications

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“…EfficientNet is one of the CNN-Based model architectures that has an advantage in its memory size and performance due to its unique method which used a scaling method that can scale uniformly which is called compound scaling [4].…”

Section: Datasetmentioning

confidence: 99%

“…Convolutional Neural Network (CNN), have been used in various image-based classification tasks such as in identifying and classifying many different types of animals the way CNN classifies images is similar to the neuron that is found in the brain with many nodes, layers, and activation function that ends with an output, the name Convolutional come from the fact that CNN has several convolutional layers that can automatically find an image feature from a process called training, there are many different types of CNN-Based model architecture such as VGG [3], EfficientNet [4] EfficientNetV2 [5], Xception [6].…”

Section: Introductionmentioning

confidence: 99%

“…Another previous study shows a model that was made with a compound model scaling convolutional neural network, called EfficientNetB0 to be specific. There was three training process and the best one has an accuracy of 95% and a validation accuracy of 91% with 179 images out of 180 predicted correctly [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fusion of pretrained CNN models for cat breed classification: A comparative study

Hamdi,

Sunaryo,

Prasetyo

2023

E3S Web Conf.

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Cat is one of the most popular domestic animals that human has domesticated for a long time, since then, there have been many breeds that can be difficult to identify with each breed having different health issues and care requirement, to resolve this problem we used Convolutional Neural Network (CNN) a widely used artificial intelligence deep learning model that has been used in many image classification problem, in this study we explored 11 different types of CNN-Based model architecture to be used in a fusion-based technique and fine-tune the model to further increase its performance, our results show that fusion model is a promising technique in classifying cat breeds that outperforms all of the individual CNN- Based model architecture with the 3 fusion model having an accuracy of 0.9053, precision of 0.9075, recall of 0.9053, and F1 score of 0.9016, additionally, fine-tuning only shows a small effect in increasing the fusion model performance.

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Section: Datasetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fusion of pretrained CNN models for cat breed classification: A comparative study

Hamdi,

Sunaryo,

Prasetyo

2023

E3S Web Conf.

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“…Kegunaan dari Haar Feature untuk membedakan nilai beda antara hasil-hasil nilai piksel gray level ditentukan dengan cara mengurangi rata-rata nilai pada daerah terang. Sebelum himpunan dataset digunakan dalam proses pelatihan, himpunan data mengalami proses augmentasi termasuk flip acak, acak zoom, rotasi acak, meningkatkan kecerahan, dan rentang pergeseran acak [10]. Pelatihan pertama-tama harus dilakukan untuk menghasilkan pohon keputusan, yang disebut pengklasifikasi kaskade, sebagai penentu apakah suatu objek ada di setiap bingkai yang diproses.…”

Section: Menentukan Haar Featureunclassified

Sistem Deteksi Masker Menggunakan Algoritma Haar Cascade dalam Menghadapi Era New Normal

Suhirja

Jemakmun

2022

SMATIKA

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Wabah covid-19 itu berasal dari sekelompok kasus pneumonia manusia di kota Wuhan, China, pada akhir Desember 2019. Covid-19 telah menjadi wabah di negara Indonesia sejak Maret 2020. Tidak hanya di negara kita, penyebaran virus covid-19 juga telah mempengaruhi setiap negara di dunia. Oleh karena itu saat ini berbagai tempat telah menerapkan aturan khusus untuk mematuhi protokol kesehatan. Salah satunya adalah pemerintahan gubernur (pub) 2020, di mana seluruh Sumatera bagian selatan harus mengikuti protokol kesehatan dengan memakai masker. Program sistem deteksi masker ini merupakan cara untuk mengatasi kesadaran masyarakat, khususnya mahasiswa di Universitas Bina Darma, bahwa betapa pentingnya penggunaan masker saat ini. dengan memanfaatkan kecerdasan buatan penulis membuat sistem untuk mendeteksi masker. Dalam menulis program ini, penulis menggunakan python dan menggunakan algoritma haar cascade. Algoritma haar cascade ini merupakan gagasan dari Paul Viola dan Michael Jones di tahun 2001, mereka mempresentasikan sebuah makalah yang disebut “Deteksi Objek Cepat Menggunakan Perangkat Tambahan Sederhana”. Dari percobaan menggunakan metode haar cascade, sistem dapat mendeteksi orang yang memakai masker dan tidak memakai masker. pengujian ini melibatkan gambar dan video secara real-time menggunakan bounding box.

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“…Two methods have been proposed to train that acoustic data: k-Nearest Neighboor and Multilayer perceptron. Karlita et al classified cat breed with the EfficientNet-B0 pre-trained model, which resulted in more than 90% accuracy but only for the selected nine types of cats [5]. The high accuracy of 95% was proposed by Qatrunnada et al using Xception Architecture, but it was only trained for five classes [13].…”

Section: Introductionmentioning

confidence: 99%

Catbreedsnet: An Android Application for Cat Breed Classification Using Convolutional Neural Networks

Ramadhan

Setiawan

2023

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There are so many cat races in the world. Ignorance in recognizing cat breeds will be dangerous if the cat being kept is affected by a disease, which allows mishandling of the cat being kept. In addition, many cat breeds have different foods from one race to another. The problem is that a cat caretaker cannot easily recognize the cat breed. Therefore, technology needs to help a cat caretaker to treat cats appropriately. In this study, we proposed a Machine Learning approach to recognize cat breeds. This study aims to identify the cat breed from the cat images then deployed on an Android smartphone. It was tested with data from cat images of 13 races. The classification method applied in this study uses the Convolutional Neural Network (CNN) algorithm using transfer learning. The base models tested are MobilenetV2, VGG16, and InceptionV3. The results tested using several models and through several experimental scenarios produced the best classification model with an accuracy of 82% with MobilenetV2. The model with the best accuracy is then embedded in an application with the Android operating system. Then the application is named Catbreednet.

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Cat Breeds Classification Using Compound Model Scaling Convolutional Neural Networks.

Cited by 6 publications

References 5 publications

Fusion of pretrained CNN models for cat breed classification: A comparative study

Fusion of pretrained CNN models for cat breed classification: A comparative study

Sistem Deteksi Masker Menggunakan Algoritma Haar Cascade dalam Menghadapi Era New Normal

Catbreedsnet: An Android Application for Cat Breed Classification Using Convolutional Neural Networks

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