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.
The aim of this research is to prepare a set of complexes with the general formula [M(HMB)n] , where M=VO (II) , Cr(III) and Cu(II) while n=2,3,2 respectively resulting from the reaction of anew ligand [N'-(2-hydroxy-3-methoxybenzyl)-4-methylbenzohydrazide] (HMB) derived from the reaction of the tow substances (4-methylbenzohydrazide and 2-hydroxy-3-methoxy benzaldehyde) with metal ions. The prepared compounds were identified by several spectroscopic methods such as Infrared, Nuclear Magnetic Resonance and Electronic Spectra. From the results of the measurements, it was suggested that the prepared complexes have different geometries such as square planar (Cu), square pyramidal (VO) and octahedral (Cr). DFT simulations backed up
... Show MoreNumber of new polyester and polyamide are prepared as derivatives from 5,5`-(1,4-phenylene)-bis-(1,3,4-thiadiazole-2-amine) [C1], three series of heterocyclic compounds were synthesized.The first series includes the Schiff base [C2] prepared from the reaction between compound [C1] with p-hydroxy benzaldehyde in presence of acetic acid and absolute ethanol , then these derivatives have reaction with maleic anhydride , phthalic anhydride and sodium azide, respectively to obtain the compounds [C3-5] contaning (oxazepine and tetrazole) rings.The third series of compounds [C1-5] has transformed to their polymers [C6-15] by reaction with adipoyl chloride and glutroyl chloride , respectively. The reaction was followed by T.L.C and ident
... Show MoreNew Azo ligands HL1 [2-Hydroxy-3-((5-mercapto-1,3,4-thiadiazol-2-yl)diazenyl)-1-naphth aldehyde] and HL2 [3-((1,5-Dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)diazenyl)-2-hydroxy-1-naphthaldehyde] have been synthesized from reaction (2-hydroxy-1-naphthaldehyde) and (5-amino-1,3,4-thiadiazole-2-thiol) for HL1 and (4-amino-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one) for HL2. Then, its metal ions complexes are synthesized with the general formula; [CrHL1Cl3(H2O)], [VOHL1(SO4)] [ML1Cl(H2O)] where M = Mn(II), Co(II), Ni(II) and Cu(II), and general formula; [Cr(L2)2 ]Cl and [M(L2)2] where M = VO(II), Mn(II), Co(II), Ni(II) and Cu(II) are reported. The ligands and their metal complexes are characterized by phisco- chemical spectroscopic
... Show MoreThe new complexes including Cu(II), Co(II), Ni(II), Pt(IV), and Pd(II) metals with 4,4'-(((1E,1'E)-1,4-phenylenebis(methaneylylidene))bis(azaneylylidene))bis(5-(4-chlorophenyl)-4H-1,2,4-triazole-3-thione) have been synthesized of utilizing us polystyrene (PS) photostability. The supplement (0,5 w / v%) was for the production of polystyrene ( PS) in the form of tetrahydrofuran (THF). Polystyrene films were exposing irradiation (250 – 380 nm) absorption light intensity of 6.02 x 10-9 ein dm-3 s-1 at room temperature, through the changes that occur to each of viscosity average molecular weight (Mv), main chain scission (S), degree of polymerization (DPn), weight loss %, hydroxyl index (lOH), carbonyl index (ICo) determined the photo stabiliz
... Show MoreOnline learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.
Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba
... Show MoreSocial Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation. Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota
... Show MoreThe current study aims to examine the level of problems faced by university students in distance learning, in addition to identify the differences in these problems in terms of the availability of internet services, gender, college, GPA, interactions, academic cohort, and family economic status. The study sample consisted of (3172) students (57.3% females). The researchers developed a questionnaire with (32) items to measure distance learning problems in four areas: Psychological (9 items), academic (10 items), technological (7 items), and study environment (6 items). The responses are scored on a (5) point Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree). Means, standard deviations, and Multivariate Analysis of Vari
... Show MoreThe current research aimed to analyze the importance, correlation and the effect of independent variables represented by marketing variables on the dependent variable represented by local brand, through taking ENIEM as a model for this study, which represents a sensitive sector for the Algerian consumer. The results of the study evinced that the Algerian consumer has a positive image toward the brand ENIEM given marketing variables which has acquired considerable importance to this consumer. Also, the results of this study showed a statistically significant correlation between marketing variables and good perception toward the brand ENIEM, at the same time, the existence of a statistically significant effect for each of these variables o
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