Download Computer and Computing Technologies in Agriculture VII: 7th by Daoliang Li, Yingyi Chen (eds.) PDF

By Daoliang Li, Yingyi Chen (eds.)

The two-volume set IFIP AICT 419 and 420 constitutes the refereed post-conference lawsuits of the seventh IFIP TC five, WG 5.14 overseas convention on desktop and Computing applied sciences in Agriculture, CCTA 2013, held in Beijing, China, in September 2013. The one hundred fifteen revised papers offered have been rigorously chosen from a variety of submissions. They conceal a variety of attention-grabbing theories and purposes of data know-how in agriculture, together with net of items and cloud computing; simulation versions and decision-support platforms for agricultural creation; shrewdpermanent sensor, tracking, and regulate know-how; traceability and e-commerce know-how; computing device imaginative and prescient, special effects, and digital fact; the appliance of data and communique expertise in agriculture; and common info carrier expertise and repair structures improvement in rural areas.

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Read or Download Computer and Computing Technologies in Agriculture VII: 7th IFIP WG 5.14 International Conference, CCTA 2013, Beijing, China, September 18-20, 2013, Revised Selected Papers, Part I PDF

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Computer and Computing Technologies in Agriculture VII: 7th IFIP WG 5.14 International Conference, CCTA 2013, Beijing, China, September 18-20, 2013, Revised Selected Papers, Part I

The two-volume set IFIP AICT 419 and 420 constitutes the refereed post-conference court cases of the seventh IFIP TC five, WG five. 14 foreign convention on machine and Computing applied sciences in Agriculture, CCTA 2013, held in Beijing, China, in September 2013. The a hundred and fifteen revised papers awarded have been rigorously chosen from a variety of submissions.

Additional info for Computer and Computing Technologies in Agriculture VII: 7th IFIP WG 5.14 International Conference, CCTA 2013, Beijing, China, September 18-20, 2013, Revised Selected Papers, Part I

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36 J. Chen et al. Table 3. 3% Table 4. 7% The Matching Research of Strawberry Diseases Image Features 37 From the table 3, it is clear that four feature quantities(Namely C7,C8,C12,T8) reach a good performance in clustering. From the table 4, it is clear that four feature quantities(Namely C6,C12,T6,T8) reach a good performance in clustering. 2 KD-Tree Search Matching In this paper we uses 90 strawberry samples(including normal strawberry, strawberry of powdery mildew and deformity strawberry, each type samples includes 30 samples) selected three features to build 3D-Tree, three features to be matched samples of input KD-Tree search matching program.

Cn Abstract. According to the problem of the low matching accuracy rate and the low speed in the matching technology for image search, we choose the image of the strawberry diseases as the object of the research, to extract the feature of strawberry diseases image and then do cluster analysis using SPSS, and choose the feature combination according to the clustering effect. Do search matching experiments on the feature combination by KD-Tree matching algorithm respectively, and determine the characteristics combination which search matching accuracy is higher by comparing the results.

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