2022
DOI: 10.23917/khif.v8i2.16489
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Object Detection to Identify Shapes of Swallow Nests Using a Deep Learning Algorithm

Abstract: Object detection is basic research in the field of computer vision to detect objects in an image or video. the TensorFlow framework is a widely adopted framework to create object detection programs and models. In this study, an object detection program and model are designed to detect the shape of a swallow's nest which consists of three classes, namely oval, angular, and bowl. The purpose model creation is to find out the likeliness of the swallow's nest to the three classes for the swallow's nest sorting mac… Show more

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Cited by 5 publications
(4 citation statements)
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“…In the years 2020-2022, the progress of research in the classification of Swiftlet's nest was going on, where object detection was the most studied algorithm to be employed [8]. Some results have been tested for the company through the developed application, which was still a prototype.…”
Section: Deep Learning Classificationmentioning
confidence: 99%
“…In the years 2020-2022, the progress of research in the classification of Swiftlet's nest was going on, where object detection was the most studied algorithm to be employed [8]. Some results have been tested for the company through the developed application, which was still a prototype.…”
Section: Deep Learning Classificationmentioning
confidence: 99%
“…However, this average pooling was not used here. Instead, we employ the global average pooling as shown by (4), which is almost similar to average pooling [11], [15], i.e.,…”
Section: Mobilenetv2-d and Multiple Cameras For Swiftlet Nest Classif...mentioning
confidence: 99%
“…The classification of chili conditions [1], fruit quality classification [2], and classification of unwashed eggs applied to a sorting machine [3] are the examples addressed in the literature. In the case of swiftlet nest detection, swiftlet nests are classified into 3 classes, which apply CNN for feature extraction as well [4]. CNN has been used for various things, including sorting machines.…”
Section: Introductionmentioning
confidence: 99%
“…Nilai confusion matrix dapat dihitung berdasarkan contoh pada Tabel 1, serta dapat digunakan untuk menghitung nilai accuracy, precision dan recall dengan rumus masing-masing pada persamaan (10), (11), dan (12) [24].…”
Section: Evaluasiunclassified