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56 articles for “Pre-Image”
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Research ArticleOpen accessIn the abstractAutomated Fall Armyworm (Spodoptera frugiperda, J.E. Smith) Pheromone Trap Based on Machine LearningSimon H. Chiwamba, Jackson Phiri, Philip O.Y. Nkunika et al.Maize is the main food crop that meets the nutritional needs of both humans and livestock in the sub-Saharan African region. Maize crop has in the recent past been threatened by the fall armyworm (Spodoptera frugiperda, J.E Smith) which has caused considerable maize yield losses in the region. Controlling this pest requires knowledge on the time, location and extent of … …Journal of Computer Science, Vol. 15, Issue 12 · 19 Dec 2019 · 8,364 accessesView PDFCite
Research ArticleOpen accessIn the abstractFarmer-Friendly Mobile Application for Automated Leaf Disease Detection of Real-Time Augmented Data Set using Convolution Neural NetworksRishiikeshwer B. S., T. Aswin Shriram, J. Sanjay Raju et al.In farming, crops are prone to a wide variety of diseases. The impact of sudden climatic change has adverse effects on their growth, providing incubation to harmful viruses and bacteria. Diseases to crops imply a significant negative impact on health, economy and livelihood of the human population. According to the data from the Food and Agricultural Organization (FAO), an average … …Journal of Computer Science, Vol. 16, Issue 2 · 24 Aug 2019 · 8,987 accessesView PDFCite
Research ArticleOpen accessIn the abstractThermal Face Authentication with Convolutional Neural NetworkMohamed Sayed, Faris BakerMatching thermal face images as a method of biometric authentication has gained increasing interest because of its advantage of tracking a target object at night and in total darkness. Therefore, for security purposes, it has become highly favourable and has extensive applications, for instance, in video surveillance at night. The aim of this study is to present a simple and … …Journal of Computer Science, Vol. 14, Issue 12 · 10 Dec 2018 · 7,854 accessesView PDFCite
Research ArticleOpen accessIn the abstractIsolated Arabic Hand Written Letters Recognition Based on Contour Matching and Neural NetworkBajes Zeyad Aljunaeidia, Mutasem Shabib Alkhasawneh, Mohammad Ali BaniYounesComplexity of Arabic writing language makes its handwritten recognition very complex in terms of computer algorithms comparing with other languages such as English and French. The Arabic handwritten recognition has high importance in modern applications. The contour analysis of word image can extract special contour features that discriminate one character from another by the mean of vector features. This paper … …Journal of Computer Science, Vol. 14, Issue 11 · 23 Nov 2018 · 7,415 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Sensors for Monitoring Combustion Quality and Flue Gas Emissions in Power Station BoilersNallamilli P G Bhavani, Kesavan Sujatha, Ponmagal RajendranThis research work includes a combination of Fisher’s Linear Discriminant (FLD) analysis by merging Radial Basis Function (RBF) Network and Back Propagation Algorithm (BPA) for monitoring the combustion conditions of a coal fired boiler. The CCD Camera is used to capture the two dimensional flame images. The features such as images, average intensity, area, brightness and orientation etc., of the … …American Journal of Applied Sciences, Vol. 15, Issue 1 · 7 Feb 2018 · 7,552 accessesView PDFCite
Research ArticleOpen accessIn the abstractWavelet Statistical Texture Features with Orthogonal Operators Tumour Classification in Magnetic Resonance Imaging BrainR. Meenakshi, P. AnandhakumarTumors medically also called neoplasms are an abnormal mass of tissue resulting from uncontrolled proliferation or division of cells occurring in the human body. If such growth is located in the brain then it is called as brain tumor. Identification of such tumors is a major challenge in the field of medical science. Early identification of tumors prove to be … …American Journal of Applied Sciences, Vol. 10, Issue 10 · 5 Sep 2013 · 6,600 accessesView PDFCite
Research ArticleOpen accessIn the abstractLT-LBP-Based Spatial Texture Feature Extraction with Deep Learning for X-Ray ImagesPankaja Lakshmi P., Sivagami M.The novel logarithmic transformation of Local Binary Pattern (LT-LBP) for texture feature extraction is used with Deep Learning (DL) models. The Computational complexity in the DL models asymptotically increases with the data sesssst and the depth of the layers in Convolutional Neural Networks (CNN). Pre-processing the images before training the DL model holds a strong impact on the operation speed … …Journal of Computer Science, Vol. 20, Issue 1 · 18 Dec 2023 · 7,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractHow (Un)biased are Airport Security Screening Procedures? A Social-Cognitive ExperimentPoornima Madhavan, Jeremy R. BrownProblem statement: This research examined the role that social-cognitive biases such as gender biases and racial biases play in decision making processes during the screening of carry-on luggage at airports. This research is unique in that no research so far has addressed the social-psychological underpinnings of airport security screening procedures. Approach: Participants (n = 36) performed a computer simulated task … …Current Research in Psychology, Vol. 1, Issue 1 · 30 Jun 2010 · 8,009 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Networks Based Time-Delay Estimation using DCT CoefficientsSamir J. Shaltaf, Ahmad A. MohammadThis study dealt with the problem of estimating constant time delay embedded into a received signal that was noisy, delayed and damped image of a known reference signal. The received signal was filtered, normalized with respect to the peak value it achieved and then transformed by the Discrete Cosine Transform (DCT) into DCT coefficients. Those DCT coefficients that were most … …American Journal of Applied Sciences, Vol. 6, Issue 4 · 30 Apr 2009 · 7,479 accessesView PDFCite
Research ArticleOpen accessIn the abstractFine Needle Aspiration Cytology Evaluation for Classifying Breast Cancer Using Artificial Neural NetworkNor Ashidi Mat Isa, Esugasini Subramaniam, Mohd Yusoff Mashor, Nor Hayati OthmanThirteen cytology of fine needle aspiration image (i.e. cellularity, background information, cohesiveness, significant stromal component, clump thickness, nuclear membrane, bare nuclei, normal nuclei, mitosis, nucleus stain, uniformity of cell, fragility and number of cells in cluster) are evaluated their possibility to be used as input data for artificial neural network in order to classify the breast precancerous cases into four … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 7,152 accessesView PDFCite