Application of principal component analysis for rice f5 families characterization and evaluation
نویسندگان
چکیده
منابع مشابه
Sparse Structured Principal Component Analysis and Model Learning for Classification and Quality Detection of Rice Grains
In scientific and commercial fields associated with modern agriculture, the categorization of different rice types and determination of its quality is very important. Various image processing algorithms are applied in recent years to detect different agricultural products. The problem of rice classification and quality detection in this paper is presented based on model learning concepts includ...
متن کاملthe stady and analysis of rice agroclimatology in lenjan
the west of esfahan province, iran, is one of the most important agricultural areas throughout the country due to the climate variability and life-giving water of zayanderood river. rice is one of the major and economic crops in this area. the most important climatic elements in agricultural activities which should be considered include temperature, relative humidity, precipitation and wind. so...
15 صفحه اولCompression of Breast Cancer Images By Principal Component Analysis
The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most relevant information of X. These eigenvectors are called principal components [8]. Ass...
متن کاملextraction and characterization of allium irancum plant extract and its application in the green synthesis of silver nano particles and oxidation of thiocarbony1 compounds
سنتز سبز نانوذرات فلزی (nps) درسالهای اخیر توجه بسیارزیادی را به خود جلب کرده است. زیرا این پروتوکل کم هزینه وسازگار با محیط زیست از روش های استاندارد سنتز. در این پایان نامه ما گزارش میکنیم یک روش ساده و سازگار با محیط زیست برای سنتز نانوذرات نقره با استفاده از محلول آبی عصاره گیاه allium iranicum به عنوان یک عامل کاهش دهنده ی طبیعی. نانو ذرات نقره مشخص شد با استفاده از تکنیک های uv-visible، x...
Compression of Breast Cancer Images By Principal Component Analysis
The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most relevant information of X. These eigenvectors are called principal components [8]. Ass...
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: Emergent Life Sciences Research
سال: 2018
ISSN: 2395-664X,2395-6658
DOI: 10.31783/elsr.2018.417284