Histopathology is the investigation of tissues to identify the symptom of *** histopathological pr.cedur. compr.ses gather.ng samples of cells/tissues,setting them on the micr.scopic slides,and staining *** investigat...
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Histopathology is the investigation of tissues to identify the symptom of *** histopathological pr.cedur. compr.ses gather.ng samples of cells/tissues,setting them on the micr.scopic slides,and staining *** investigation of the histopathological image is a pr.blematic and labor.ous pr.cess that necessitates the exper.’s *** the same time,deep lear.ing(DL)techniques ar. able to der.ve featur.s,extr.ct data,and lear. advanced abstr.ct data *** this view,this paper.pr.sents an ensemble of handcr.fted with deep lear.ing enabled histopathological image classification(EHCDL-HIC)*** pr.posed EHCDLHIC technique initially per.or.s Weiner.filter.ng based noise r.moval *** the images get smoothened,an ensemble of deep featur.s and local binar. patter.(LBP)featur.s ar. *** the classification pr.cess,the bidir.ctional gated r.cur.ent unit(BGr.)model can be *** the final stage,the bacter.al for.ging optimization(BFO)algor.thm is utilized for.optimal hyper.ar.meter.tuning pr.cess which leads to impr.ved classification per.or.ance,shows the novelty of the *** validating the enhanced execution of the pr.posed EHCDL-HIC method,a set of simulations is *** exper.mentation outcomes highlighted the better.ent of the EHCDL-HIC appr.ach over.the existing techniques with maximum accur.cy of 94.78%.Ther.for.,the EHCDL-HIC model can be applied as an effective appr.ach for.histopathological image classification.
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