Innovation Strategies: Challenges or Opportunities in Software Development Teams

Asil, Hasan

doi:10.3923/jse.2013.151.155

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…The greedy learning procedure has two advantages [27]: firstly, it provides for proper network initialization and therefore it reduces the difficulty of selecting the parameters (which may lead to the selection of local optima); secondly, the learning process is unsupervised, without a need for a class label. Hence, the training need for the labeled data is avoided [28]. However, the development of a DBN model icurs heavy computational costs because it is not known how to approximate the maximum training likelihood for the model optimization [29].…”

Section: The Proposed Methodsmentioning

confidence: 99%

Proposing a new method of image classification based on the AdaBoost deep belief network hybrid method

Bagherzadeh

Asil

2019

TELKOMNIKA

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Image classification has different applications. Up to now, various algorithms have been presentedfor image classification. Each of these methods has its own weaknesses and strengths. Reducing error rate is an issue which many researches have been carried out about it. This research intends to optimize the problem with hybrid methods and deep learning. The hybrid methods were developed to improve the results of the single-component methods. On the other hand, a deep belief network (DBN) is a generative probabilistic modelwith multiple layers of latent variables and is used to solve the unlabeled problems. In fact, this method is anunsupervised method, in which all layers are one-way directed layers except for the last layer. So far, various methods have been proposed for image classification, and the goal of this research project was to use a combination of the AdaBoost method and the deep belief network method to classify images. The other objective was to obtain better results than the previous results. In this project, a combination of the deep belief network and AdaBoost method was used to boost learning and the network potential was enhanced by making the entire network recursive. This method was tested on the MINIST dataset and the results were indicative of a decrease in the error rate with the proposed method as compared to the AdaBoost and deep belief network methods.

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Section: The Proposed Methodsmentioning

confidence: 99%

Proposing a new method of image classification based on the AdaBoost deep belief network hybrid method

Bagherzadeh

Asil

2019

TELKOMNIKA

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“…Hasil penelitian ini sejalan dengan penelitian yang dilakukan oleh Smith et al (2019), yang menyatakan bahwa pengujian yang komprehensif dan berlapis-lapis sangat penting untuk memastikan bahwa aplikasi perangkat lunak berfungsi tanpa kesalahan. Penelitian ini juga didukung oleh temuan Jones (2020), yang menekankan pentingnya uji integrasi dan sistem dalam mengidentifikasi dan memperbaiki potensi masalah sebelum aplikasi diluncurkan.…”

Section: Pembahasanunclassified

Perancangan Sistem Informasi E-Commerce untuk Usaha Mikro Kecil dan Menengah (UMKM) Furnitur

Alief,

Chotijah

2024

SLJIL

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Usaha Mikro Kecil dan Menengah mempunyai peranan penting dalam perekonomian negara Indonesia. Permasalahan yang dihadapi oleh UMKM adalah keterbatasan teknologi dan inovasi dan kurangnya akses ke pasar yang lebih luas. Tujuan dari penelitian ini adalah untuk menyelesaikan permasalahan tersebut yaitu dengan mengembangkan aplikasi toko daring atau e-commerce. Metode yang digunakan adalah studi literatur dan metode pengembangan perangkat lunak menggunakan metode waterfall. Pembangunan aplikasi ini menggunakan bahasa pemrograman JavaScript dan MongoDB sebagai basis data. Hasil yang diperoleh pada perancangan dan pengembangan aplikasi dapat mempermudah pelaku UMKM dalam mengembangkan usahanya ke pasar yang lebih luas dengan memanfaatkan teknologi terkini.

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Investigation on Hadoop-based Distributed Search Engine

Chen¹,

Xiangyang²

2014

J. of Software Engineering

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Innovation Strategies: Challenges or Opportunities in Software Development Teams

Cited by 3 publications

References 2 publications

Proposing a new method of image classification based on the AdaBoost deep belief network hybrid method

Proposing a new method of image classification based on the AdaBoost deep belief network hybrid method

Perancangan Sistem Informasi E-Commerce untuk Usaha Mikro Kecil dan Menengah (UMKM) Furnitur

Investigation on Hadoop-based Distributed Search Engine

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