MATLAB神經(jīng)網(wǎng)絡(luò)圖像識別高識別率代碼
創(chuàng)新互聯(lián)公司長期為成百上千客戶提供的網(wǎng)站建設(shè)服務(wù),團(tuán)隊從業(yè)經(jīng)驗(yàn)10年,關(guān)注不同地域、不同群體,并針對不同對象提供差異化的產(chǎn)品和服務(wù);打造開放共贏平臺,與合作伙伴共同營造健康的互聯(lián)網(wǎng)生態(tài)環(huán)境。為黑河企業(yè)提供專業(yè)的網(wǎng)站設(shè)計、成都做網(wǎng)站,黑河網(wǎng)站改版等技術(shù)服務(wù)。擁有十年豐富建站經(jīng)驗(yàn)和眾多成功案例,為您定制開發(fā)。I0=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\0 (1).png')); I1=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\1 (1).png')); I2=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\2 (1).png')); I3=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\3 (1).png')); I4=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\4 (1).png')); I5=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\5 (1).png')); I6=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\6 (1).png')); I7=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\7 (1).png')); I8=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\8 (1).png')); I9=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\9 (1).png')); %以上數(shù)據(jù)都是歸一化好的數(shù)據(jù)。 P=[I0',I1',I2',I3',I4',I5',I6',I7',I8',I9']; T=eye(10,10); %%bp神經(jīng)網(wǎng)絡(luò)參數(shù)設(shè)置 net=newff(minmax(P),[144,200,10],{'logsig','logsig','logsig'},'trainrp'); net.inputWeights{1,1}.initFcn ='randnr'; net.layerWeights{2,1}.initFcn ='randnr'; net.trainparam.epochs=5000; net.trainparam.show=50; net.trainparam.lr=0.001; net.trainparam.goal=0.0000000000001; net=init(net); %%%訓(xùn)練樣本%%%% [net,tr]=train(net,P,T); PIN0=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\4 (2).png')); PIN1=pretreatment(imread('Z:\data\PictureData\TestCode\SplitDataTest\3 (2).png')); P0=[PIN0',PIN1']; T0= sim(net ,PIN1') T1 = compet (T0) d =find(T1 == 1) - 1 fprintf('預(yù)測數(shù)字是:%d\n',d); %有較高的識別率
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