Plant Disease Detection

Manvi, Goutami G; Gayana, K N; Sree, G Ramya; Divyanjali, K; Patil, Dr Kirankumari

doi:10.22214/ijraset.2022.43221

Cited by 2 publications

(2 citation statements)

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“…Bangunan pada era industrial menonjolkan penggunaan material yang jujur. Jujur dalam arti material tersebut ditunjukkan apa adanya, tanpa finishing (Manvi, 2017). Prinsip fungsional dan efisien memandu pengembangan bangunan industri modern sepanjang karir arsitek-arsitek tersebut.…”

Section: Prinsip Open Plan Efektivitas Dan Fungsi Bangunan Industri A...unclassified

Pengenalan Bangunan Industri Bagi Pelajar Kota Lhokseumawe

Dela andriani,

Deni,

Hendra

et al. 2024

MJM

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Bangunan Industri bagi pelajar kota Lhokseumawe khususnya merupakan sosok wujud bangunan yang sulit untuk dijamah keberadaannya. Melalui kegiatan pengabdian ini dilakukan observasi langsung ke lokasi bangunan industri PT. Pupuk Iskandar Muda Kota Lhokseumawe menjadi suatu yang menarik sebagai moda pemicu membudayakan generasi arsitek dimasa yang akan datang. Profesi akademisi arsitektur merupakan profesi yang memiliki tanggung jawab terhadap pembelajaran dan kualitas hidup manusia dalam menjawab permasalahan ruang dalam menampung aktivitas yang ada, khususnya pada bangunan industri. Untuk menjawab permasalahan tersebut, sebagai pendekatan dari pihak akademisi merasa terpanggil untuk mengadakan kegiatan pengenalan bangunan industri pada pelajar setempat sebagai referensi intelktuali arsitektur mereka. Kegiatan pengabdian masyarakat terbagi dalam dua bagian, pertama yaitu pengenalan wujud fisik bangunan atas ruang-ruang yang tercipta dari aspek ide strukturasi. Kedua, kegiatan pengenalan teknis tentang pemahaman bangunan industri melalui ide pragmatis fungsionalitas ruang arsitektur. Kegiatan pengenalan bangunan industri dilakukan secara argumentatif dan interaktif hanya menyasar ikatan intelektual pelajar, berharap mereka mulai memiliki rasa keingintahuan yang kuat sebagai nilai mental tumbuhnya benih minat mereka dalam bidang Ilmu Arsitektur. Dampak yang diterima dengan adanya pengenalan profesi arsitek pada pelajar Kota Lhokseumawe adalah terlihatnya ketertarikan mereka dalam mengikuti kegiatan dengan fokus, interaktif dan komunikatif dengan harapan bahwa keilmuan arsitektur yang mendapat tempat di pikiran mereka di masa depan.

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Section: Prinsip Open Plan Efektivitas Dan Fungsi Bangunan Industri A...unclassified

Pengenalan Bangunan Industri Bagi Pelajar Kota Lhokseumawe

Dela andriani,

Deni,

Hendra

et al. 2024

MJM

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“…Thus, it is imperative to investigate possible fast detection, control, and treatment options. Traditional naked eye inspection is the first line of defense toward disease diagnosis [ 3 ], but it is prone to errors [ 4 , 5 ]. Furthermore, farmers can employ the wrong type of treatment method or chemical [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Classification of Corn Diseases from Leaf Images Using Deep Transfer Learning

Fraiwan

Faouri

Khasawneh

2022

Plants

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Protecting agricultural crops is essential for preserving food sources. The health of the plants plays a major role in impacting the yield of the agricultural output and results in significant economic loss. This is especially important in small-scale and hobby farming products such as fruits. Grapes are an important and widely cultivated plant especially in the Mediterranean region, with over $189 billion global market value. They are consumed as fruits as well as in other manufactured forms (e.g., drinks and sweet food products). However, much like other plants, grapes are prone to a wide range of diseases that require the application of immediate remedies. Misidentifying these diseases can result in poor disease control and great losses (i.e., 5–80% crop loss). Existing computer-based solutions may suffer from low accuracy, may require high overhead, are poorly deployable, and are prone to changes in image quality. The work in this paper aimed at utilizing ubiquitous technology to help farmers combat plant diseases. Particularly, deep learning artificial intelligence image-based applications were used to classify three common grape diseases—black measles, black rot, and isariopsis leaf spot. In addition, a fourth healthy class was included. A dataset of 3639 grape leaf images (1383 black measles, 1180 black rot, 1076 isariopsis leaf spot, and 423 healthy) was used. These images were used to customize and retrain eleven convolutional network models to classify the four classes. Thorough performance evaluation revealed that it is possible to design pilot and commercial applications that have accuracies that satisfy field requirements. The models achieved consistently high performance values (>99.1%).

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Plant Disease Detection

Cited by 2 publications

References 0 publications

Pengenalan Bangunan Industri Bagi Pelajar Kota Lhokseumawe

Pengenalan Bangunan Industri Bagi Pelajar Kota Lhokseumawe

Classification of Corn Diseases from Leaf Images Using Deep Transfer Learning

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