本科生論文樣本標(biāo)準(zhǔn)格式-展示頁
2024-08-19 16:21本頁面
【正文】 錯(cuò)誤！未定義書簽。 錯(cuò)誤！未定義書簽。 錯(cuò)誤！未定義書簽。 錯(cuò)誤！未定義書簽。 錯(cuò)誤！未定義書簽。 錯(cuò)誤！未定義書簽。 錯(cuò)誤！未定義書簽。 錯(cuò)誤！未定義書簽。 小結(jié) 錯(cuò)誤！未定義書簽。 基于機(jī)器視覺的種蛋孵化成活性檢測(cè) 錯(cuò)誤！未定義書簽。 種蛋篩選和孵化成活性檢測(cè)硬件系統(tǒng)建立 錯(cuò)誤！未定義書簽。 存在問題 錯(cuò)誤！未定義書簽。 用小四號(hào)黑體字，頂左。(3) Egg shape index and radius differences are extracted as shape feature parameters, a twostep shape measurement method is proposed based on machine vision, moment technique and neural network. An improved immune GA algorithm is put forward, which is used to optimize topology structure of LMBP neural network for detecting quality of hatching egg automatically. Key Words: Fertility identification。Identifying quality and fertility of hatching eggs are an important and hard work in the farms. Manual inspection suffers from visual stress and tiredness and is low accuracy and timeconsuming. An automatic and practical detection system based on machine vision system and ANN is developed instead of manual inspection of hatching egg for improving detecting accuracy and effciency. 1. The machine vision hardware system is built for identifying exterior quality and fertility of hatching egg .The light source and background color are found out through a lot of experiments. Camera calibration is done for correcting image distortion, and its accuracy is able to match the demand of identifying exterior quality of hatching egg. 2. Based on machine vision technique, criterion is proposed for prehensive evaluating egg’s exterior quality by weight, shape, eggshell defect feature and eggshell color, and method of egg quality classification is developed. (1) The projection area of egg image is extracted by 0order moment and used to classify egg weight instead of metage. The classification accuracy is % for bigger eggs, % for normal eggs, and % for smaller eggs. (2) Threshold recognition and 8connected boundary tracking method are bined to extract the defect feature on eggshell, and its classification accuracy is % for cracked eggs, % for dirt stained, blood spotted eggs and % for normal eggs.用小四號(hào)Times New Roman字， 注 意：每個(gè)詞首字母大寫。Based on Machine Vision SystemAbstract內(nèi)容用小四號(hào)Times New Roman字。題名下面空一行。用小四號(hào)黑體字，頂左。注 意：盡量選用主題詞表中的詞。以種蛋色度頻度值為特征參數(shù)，用優(yōu)化后的BP神經(jīng)網(wǎng)絡(luò)檢測(cè)種蛋孵化成活性，對(duì)孵化早期、%、%和100%。3．參照人工照蛋時(shí)間，對(duì)孵化早期、中期和后期的種蛋胚胎成活性檢測(cè)方法進(jìn)行了系統(tǒng)研究。內(nèi)容用小四號(hào)宋體字。過長蛋、%、%%，%。(3) 提出基于機(jī)器視覺、矩和神經(jīng)網(wǎng)絡(luò)技術(shù)，以種蛋蛋形指數(shù)及蛋徑差為檢測(cè)指標(biāo)的蛋形分步檢測(cè)方法。(1) 提出利用種蛋圖像零階矩計(jì)算圖像投影面積代替重量稱量的方法，檢測(cè)結(jié)果與實(shí)際稱量值間有良好的相關(guān)性，過大蛋、正常蛋、%、%%。通過對(duì)比試驗(yàn)研究，確定了圖像采集時(shí)的最佳光源和背景顏色；對(duì)種蛋篩選硬件系統(tǒng)進(jìn)行了標(biāo)定，標(biāo)定精度能滿足種蛋外觀品質(zhì)檢測(cè)要求。通過對(duì)基于機(jī)器視覺的種蛋篩選和孵化成活性檢測(cè)方法的系統(tǒng)研究，建立了種蛋篩選和孵化成活性自動(dòng)檢測(cè)系統(tǒng)。摘 要入孵前種蛋篩選以及種蛋孵化過程中胚胎成活性檢測(cè)是孵化工作的重要技術(shù)環(huán)節(jié)。一般不宜超過300字，英文摘要一般不宜超過250個(gè)實(shí)詞。字間空四個(gè)空格，下面空一行。畢業(yè)設(shè)計(jì)封面可參照此修改。（但一個(gè)學(xué)院只能選擇一種）。關(guān)于畢業(yè)論文（設(shè)計(jì)）封面格式的說明各學(xué)院有的論文標(biāo)題長或有副標(biāo)題，按照本科畢業(yè)論文統(tǒng)一封面格式打不下或不美觀。因此，附兩個(gè)封面樣本（附后）供選擇。論文標(biāo)題可視字?jǐn)?shù)多少自行調(diào)整字的大小及字間距，以美觀為宜。附：畢業(yè)論文（設(shè)計(jì)）封面樣本1 畢業(yè)論文（設(shè)計(jì)）封面樣本2 初號(hào)隸書，字間距1磅本科畢業(yè)論文二號(hào)隸書居中論文題目 學(xué) 院： 專 業(yè)： 小二號(hào)隸書居中學(xué) 號(hào)：姓 名：指導(dǎo)教師：職 稱： 論文提交日期：二ОО七年六月 本科畢業(yè)論文該處打印論文題目學(xué) 院：專 業(yè)：姓 名： 學(xué) 號(hào)：指導(dǎo)教師：職
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