This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specific synthetic PAN bands, notably PAN10, PAN2, and PAN9, demonstrate superior performance in image fusion and classification tasks. This study underscores the significance of selecting fusion algorithms and panchromatic bands tailored to applications, with Support Vector Machine classifiers showcasing resilience across diverse fusion methods. Even though the PAN8 band has exhibited lower overall accuracy, it is helpful in effectively delineating some land cover classes.
Abstract
Despite the fact of the importance and effectiveness of supporting the pricing policy for agriculture sector in Iraq, but this policy has stopped in supporting those agriculture production needs, and it was confined to support the final product only, and supporting the strategic corps exclusively after the U.S. Invasion in 2003, but after 2008 the state has returned to support some of this policy activities through providing financial loans through the agricultural initiative campaign, with trillions of iraqi dinars without any use, also providing support to some of the agricultural production needs such as fertilizers , tractors and agricultural combines, in addition supporting the pricing policy for the
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
... Show MoreThis study has been carried out in the Station of Poultry Researches which is affiliated to the General Office of Agricultural Researches / Ministry of Agriculture during the period from 01/04/2018 to 14/05/2018 there are 300 one day old chick of type (Ross 308) used in this study, and has been fed on diets which green tea powder (Camellia sinensis) has been added to it with the levels 0.5 , 1 , 1.5 , 2 g/kg as a feed for the treatments T 2 , T 3 , T 4 and T 5 respectively and compared to the control treatment T 1 which is devoid of addition, every treatment included three replicates each one has 20 birds in order to study the effect of adding a various levels of green tea powder (Camellia sinensis) to the diet on the productive performance
... Show MoreBackground/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
... Show MoreA systematic approach is presented to achieve the stable grasping of objects through a two-finger robotic hand, in which each finger cavity was filled with granular media. The compaction of the latter, controlled by vacuum pressure, was used to adjust the structural and contact stiffness of the finger. The grasping stability was studied under the concurrent effect of an external torque and applied vacuum pressure. Stable grasping was defined as the no slippage condition between the grasped object and the two fingers. Three control schemes were adopted and applied experimentally to ensure the effectiveness of the grasping process. The results showed that stable and unstable grasping regions exist for each combination of applied torqu
... Show MoreThis paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b
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