The Paper focuses on analysing neural network models that are used for semantically classifying tabular customer datasets. Additionally, we propose a custom neural network architecture to analyze tabular datasets and ...
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Wireless sensor networks (WSNs) are normally conveyed in arbitrary regions with no security. The source area uncovers significant data about targets. In this paper, a plan dependent on the cloud utilising data publish...
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The classification of walnuts in the dry areas of Ganquan Township, Awati County, Xinjiang, is investigated in this research using traditional approaches, remote sensing photos taken by satellite, and convolutional ne...
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The digital era has made seamless sharing and keeping of media such as images on cloud platforms an integral part of our lives. Still, there is a big issue about user privacy and data security in these repositories. W...
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We investigate the problem of finding a spanning tree of a set of n moving points in Rdim that minimizes the maximum total weight (under any convex distance function) or the maximum bottleneck throughout the motion. T...
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The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain *** brain tumor is characterized by an anomalous proliferation of brain c...
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The objective of this research is to examine the use of feature selection and classification methods for distinguishing different types of brain *** brain tumor is characterized by an anomalous proliferation of brain cells that can either be benign or *** tumors are misdiagnosed due to the variabil-ity and complexity of lesions,which reduces the survival rate in ***-sis of brain tumors via computer vision algorithms is a challenging *** and classification of brain tumors are currently one of the most essential surgical and pharmaceutical *** brain tumor identi-fication techniques require manual segmentation or handcrafted feature extraction that is error-prone and *** the proposed research work is mainly focused on medical image processing,which takes Magnetic Resonance Imaging(MRI)images as input and performs preprocessing,segmentation,fea-ture extraction,feature selection,similarity measurement,and classification steps for identifying brain ***,the medianfilter is practically applied to the input image to reduce the *** graph-cut segmentation technique is used to segment the tumor *** texture feature is extracted from the output of the segmented *** extracted feature is selected by using the Ant Colony Opti-mization(ACO)algorithm to improve the performance of the classifi*** prob-abilistic approach is used to solve computing *** Euclidean distance is used to calculate the degree of similarity for each extracted *** selected feature value is given to the Relevance Vector Machine(RVM)which is a multi-class classification ***,the tumor is classified as abnormal or *** experimental result reveals that the proposed RVM technique gives a better accuracy range of 98.87%when compared to the traditional Support Vector Machine(SVM)technique.
This research aims to develop a new approach to increase the safety and reliability of Autonomous Vehicle (AV) through the proposed risk assessment framework, supported by the trust evaluation approach derived from a ...
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Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,...
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Optoelectronic devices are advantageous in in-memory light sensing for visual information processing,recognition,and storage in an energy-efficient ***,in-memory light sensors have been proposed to improve the energy,area,and time efficiencies of neuromorphic computing *** study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor(MOS)charge-trapping memory structure—the basic structure for charge-coupled devices(CCD)—and showing its suitability for in-memory light sensing and artificial visual *** memory window of the device increased from 2.8 V to more than 6V when the device was irradiated with optical lights of different wavelengths during the program ***,the charge retention capability of the device at a high temperature(100 ℃)was enhanced from 36 to 64%when exposed to a light wavelength of 400 *** larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al_(2)O_(3)/MoS_(2) interface and in the MoS_(2) layer.A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the *** array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91%*** study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception,adaptive parallel processing networks for in-memory light sensing,and smart CCD cameras with artificial visual perception capabilities.
Image processing,agricultural production,andfield monitoring are essential studies in the researchfi*** diseases have an impact on agricultural production and *** disease detection at a preliminary phase reduces economi...
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Image processing,agricultural production,andfield monitoring are essential studies in the researchfi*** diseases have an impact on agricultural production and *** disease detection at a preliminary phase reduces economic losses and improves the quality of *** identifying the agricultural pests is usually evident in plants;also,it takes more time and is an expensive technique.A drone system has been developed to gather photographs over enormous regions such as farm areas and *** atmosphere generates vast amounts of data as it is monitored closely;the evaluation of this big data would increase the production of agricultural *** paper aims to identify pests in mango trees such as hoppers,mealybugs,inflorescence midges,fruitflies,and stem *** of the massive volumes of large-scale high-dimensional big data collected,it is necessary to reduce the dimensionality of the input for classify-ing *** community-based cumulative algorithm was used to classify the pests in the existing *** proposed method uses the Entropy-ELM method with Whale Optimization to improve the classification in detecting pests in *** Entropy-ELM method with the Whale Optimization Algorithm(WOA)is used for feature selection,enhancing mango pests’classification *** Vector Machines(SVMs)are especially effective for classifying while users get var-ious classes in which they are *** are created as suitable classifiers to categorize any dataset in Big data *** proposed Entropy-ELM-WOA is more capable compared to the existing systems.
In today's world the internet has ingrained itself deeply into our lives, and web searching has become essential for people of all ages, locations, and occupations. However, due to the rise in internet usage, ther...
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