Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven classifiers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classification accuracy and parameters is suggested. They provide the same set of characteristics to discover and verify which classifier yields the best classification with our new proposed approach of “hybrid learning.” To achieve this, the performance of classifiers was assessed depending on a genuine dataset that was taken by our camera system. The simulation results show that the support vector machine (SVM) has a mean square error of 0.011, a total accuracy ratio of 98.80%, and an F1 score of 0.99. Moreover, the results show that the LR classifier has a mean square error of 0.035 and a total ratio of 96.42%, and an F1 score of 0.96 comes in the second place. The ANN classifier has a mean square error of 0.047 and a total ratio of 95.23%, and an F1 score of 0.94 comes in the third place. Furthermore, RF, WKNN, DT, and NB with a mean square error and an F1 score advance to the next stage with accuracy ratios of 91.66%, 90.47%, 79.76%, and 75%, respectively. As a result, the main contribution is the enhancement of the classification performance parameters with images of varying brightness and clarity using the proposed hybrid learning approach.
Chukar partridge Alectoris chukar (Gray, 1830) is the only species of the 46 species of the genus Alectoris to be found in Iraq. At least there are fourteen subspecies of chukar were described from east Europe, the Middle East and west Asia, two of them were known to be found in Iraq, A.c. Kurdestanica (Meinertzhagen, 1923) from Alpine bio-geographical zone of altitude more than 2000m high, and A.c. werae Zarundny and Loudon, 1904, from the foothills of altitude not more than 400m. In between these two regions, there is another bio-geographical region known as the Irano-toranian zone 400-2000m high. Using morphological, ecological, behavioural, reproduction and hybridization criteria this study discove
... Show MoreThe Carbonate-clastic succession in this study is represented by the Shuaiba and Nahr Umr Formations deposited during the Albian - Aptian Sequence. The present study includes petrography, microfacies analyses, and studying reservoir characterizations for 5 boreholes within West Qurna oil field in the study area. According to the type of study succession (clastic – Carbonate) there are two types of facies analyses:-Carbonate facies analysis, which showed five major microfacies were recognized in the succession of the Shuaiba Formation, bioclastic mudstones to wackstone, Orbitolina wackestone to packstone, Miliolids wackestone, Peloidal wackestone to packstone and mudstone to wackestone identified as an open shelf toward the deep basin.
... Show MoreIn this research, the structural behavior of reinforced concrete columns made of normal and hybrid reactive powder concrete (hybrid by steel and polypropylene fibers) subjected to chloride salts with concentration was 8341.6 mg/l. The study consists of two parts, the first one is experimental study and the second one is theoretical analysis. Three main variables were adopted in the experimental program; concrete type, curing type and loading arrangement. Twenty (120x120x1200) mm columns were cast and tested depending on these variables. The samples were reinforced using two different bars; Ø8 for ties and Ø12 with minimum longitudinal reinforcement (0.01Ag). The specimens were divided into two main groups based o
... Show MoreIn this paper we proposes the philosophy of the Darwinian selection as synthesis method called Genetic algorithm ( GA ), and include new merit function with simple form then its uses in other works for designing one of the kinds of multilayer optical filters called high reflection mirror. Here we intend to investigate solutions for many practical problems. This work appears designed high reflection mirror that have good performance with reduction the number of layers, which can enable one to controlling the errors effect of the thickness layers on the final product, where in this work we can yield such a solution in a very shorter time by controlling the length of the chromosome and optimal genetic operators . Res
... Show MoreBackground The study covered thirty-three species which grown wildly in Iraq and a comparative study for all kinds of morphological characters were done. Principal Findings The most stable and important taxonomic characters were pointed out, diagrams, illustrations, scheduals, micrographs were also documented. Stamens, nutlets, basal leaves, bracts, bracteoles, calyces, corollas and their trichomes were very important taxanomic characters. The trichomes were variable in variable species therefore used as a diagnostic characters for the species. Conclusions New species Salvia margasurica Al-Musawi & Al-Hussaini was suggested to be new record for science. Keywords: Salvia, Morphology, Spec. Nov.
In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.
Celery and coriander are vastly applied in modern medicine and traditionally because various medicinal and nutritional benefits depend on their medicinal characteristics. The study aimed to detect, isolate and compare extracts contents of phenolic acids (caffeic and p-coumaric acids) in ethyl acetate fraction of fresh and dry aerial parts of coriander (Coriandrum sativum L.) and celery (Apium graveolens L.) of the Apiaceae family. The extraction of these constituents was carried out by maceration method using 70% ethanol and fractionation was done by using petroleum ether, and ethyl acetate. The existence of caffeic and p-coumaric acids in aerial part extracts of two plants was identified by thin-layer chromatography (TLC) and high-
... Show MoreAims: This study was done to investigate the effect of low energy laser therapy on bone healing at the extraction site. Materials and methods:(24) male albino rats were exposed to the extraction procedure of the maxillary first molar on the first day of a seven day experiment and these animals were divided into two main groups; the control group and the laser group. The laser experiment involved using (Ga-As infrared diode laser) from optodent by directing the probe over the extraction site. The control group consisted of 4 rats, and the laser group was subdivided into 5 subgroups of 4 rats each. The laser dose was as follows: B1: a single dose of 5 minutes immediately after extraction.,
... Show MorePolynomial IIR digital filters play a crucial role in the process of image data compression. The main purpose of designing polynomial IIR digital filters of the integer parameters space and introduce efficient filters to compress image data using a singular value decomposition algorithm. The proposed work is designed to break down the complex topic into bite-sized pieces of image data compression through the lens of compression image data using Infinite Impulse Response Filters. The frequency response of the filters is measured using a real signal with an automated panoramic measuring system developed in the virtual instrument environment. The analysis of the output signal showed that there are no limit cycles with a maximum radius
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