It is so much noticeable that initialization of architectural parameters has a great impact on whole learnability stream so that knowing  mathematical properties of dataset results in providing neural network architecture a better expressivity and capacity. In this paper, five random samples of the Volve field dataset were taken. Then a training set was specified and the persistent homology of the dataset was calculated to show impact of data complexity on selection of multilayer perceptron regressor (MLPR) architecture. By using the proposed method that provides a well-rounded strategy to compute data complexity. Our method is a compound algorithm composed of the t-SNE method, alpha-complexity algorithm, and a persistence barcod

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

FG Mohammed, HM Al-Dabbas, Science International, 2018 - Cited by 2

Optic Disc (OD) localization is a basic step for the screening, identification and appreciation of the risk of diverse ophthalmic pathologies such as glaucoma and diabetic retinopathy.In fact, the fundamental step towards an exact OD segmentation process is the success of OD localization. This paper proposes a fully automatic procedure for OD localization based on two of the OD most relevant features  of high-intensity value and vasculature convergence. Merging ofthese two features renders the proposed method capable of localizing the OD within the variously complicated environments such as the faint disc boundary, unbalanced shading, and the existence of retinal pathologies like cotton wall and exudates,which usually share the same

     A quantitative description of microstructure governs the characteristics of the material. Various heat and excellent treatments reveal micro-structures when the material is prepared. Depending on the microstructure, mechanical properties like hardness, ductility, strength, toughness, corrosion resistance, etc., also vary. Microstructures are characterized by morphological features like volume fraction of different phases, particle size, etc. Relative volume fractions of the phases must be known to correlate with the mechanical properties. In this work, using image processing techniques, an automated scheme was presented to calculate relative volume fractions of the phases, namely Ferrite, Martensite, and Bainite, present in the

 Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The

 Pan sharpening (fusion image) is the procedure of merging suitable information from two or more images into a single image. The image fusion techniques allow the combination of different information sources to improve the quality of image and increase its utility for a particular application. In this research, six pan-sharpening method have been implemented between the panchromatic and multispectral images, these methods include Ehlers, color normalize, Gram-Schmidt, local mean and variance matching, Daubechies of rank two and Symlets of rank four  wavelet transform. Two images captured by two different sensors such as landsat-8 and world view-2 have been adopted to achieve the fusion purpose. Different fidelity metric like MS

The Zubair Formation is the most significant sandstone reservoir in Iraq which deposited during the Barremian. The study area is located in the central part of Iraq at the Kifl oil field, in the northern part of the Mesopotamian Zone.

The petrographic study showed that quartz mineral is the main component of the sandstone in Zubair Formation with very low percentage of feldspar and rare rock fragments to classified as quartz arenite sandtone. There are five lithologic changes (lithofacies) that have characterized the studied succession: - well sorted quartz arenite, poorly sorted quartz arenite, poorly sorted graywacke, sandy shale, and shale.  These lithofacieses were deposited in the deltaic environments as three associate

Carbon monoxide (CO) plays an important indirect greenhouse gases due to its influences on the budgets of hydroxyl radicals (OH) and Ozone (O3). The atmospheric carbon monoxide (CO) observations can only be made on global and continental scales by remote sensing instruments situated in space. One of instrument is the Measurements of Pollution in the Troposphere (MOPITT), which is designed to measure troposphere CO and CH4 by use of a nadir-viewing geometry and was launched aboard the Earth Observing System (EOS) Terra spacecraft on 18 December 1999. Results from the analysis of the retrieved monthly (1ºх1º) spatial grid resolution, from the MOPITT data were utilized to analyze the distribution of CO surface mixing ratio in Iraq for th