Textured crop的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列包括價格和評價等資訊懶人包

另外網站發現textured crop 的熱門影片 - TikTok也說明:在TikTok 上發現與textured crop有關的短片。 查看以下創作者的熱門內容:Man Barbers (@manbarbersph), 12Pell(@12pell), Kelechi Asonye(@kele_kutz), ...

國立臺灣科技大學 資訊工程系 花凱龍所指導 陳文柏的 基於合成分析之小樣本視覺深度學習技術 (2020),提出Textured crop關鍵因素是什麼,來自於defect detection、anomaly detection、memory auto-encoder、image-to-image translation、image synthesis、generative adversarial networks。

而第二篇論文國立屏東科技大學 植物醫學系所 林盈宏、林鉉凱所指導 黃承洧的 雷射去濕法誘導金屬奈米粒子及其對炭疽病菌之抗菌效果研究 (2020),提出因為有 雷射去濕、局部表面電漿共振、雙峰吸收光譜、銀銅共晶系統、非農藥防治的重點而找出了 Textured crop的解答。

最後網站Soil Survey of ... [various Counties, Etc.]. - 第 41 頁 - Google 圖書結果則補充:They have a medium - textured and grown in the county . ... This pan restricts the Use of crop residue and green - manure crops helps to im- downward ...

接下來讓我們看這些論文和書籍都說些什麼吧:

除了Textured crop,大家也想知道這些:

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基於合成分析之小樣本視覺深度學習技術

為了解決Textured crop的問題,作者陳文柏 這樣論述:

In the past decade, the computer vision community witnessed the deep learning revolution that fueled several breakthroughs in the field, solving various visual tasks that were previously intractable. However, these breakthroughs were mostly a product of very deep networks with millions of parameter

s and large amounts of annotated data required to train it. This requirement makes it difficult to adopt these models in domains where several constraints hinder the collection of a large and diverse annotated data sets. In this thesis, I present novel solutions to the problems on anomaly detection

and semantic image manipulation under three different data constraint settings: (1) In the setting where the data have limited coverage, I propose paMAE, an anomaly detection model that incorporates an external memory and a deep spatial perceptual distance that is more robust to shifts and small ina

ccuracies, which can stem from the lack of data coverage. This makes it more suitable for determining anomalies especially in highly textured surfaces. (2) In the setting where data are noisy, I propose TrustMAE, an anomaly detection model that uses a novel trust-region memory updating scheme to kee

p noise from polluting the model. (3) In the setting where the data are not available at all times, I propose IncrementalGAN, a model for image translation that can incrementally learn new domains while still retaining old domains without requiring any data from the old domains. Our proposed methods

follow the framework of analysis-by-synthesis, wherein we leverage synthesizing and reconstructing images to provide ``annotation-free'' supervision to the model in learning meaningful representations that are useful for the target visual task. Our proposed methods perform competitively compared to

existing approaches and achieve state-of-the-art performance in select benchmark tasks, despite the data constraints.

雷射去濕法誘導金屬奈米粒子及其對炭疽病菌之抗菌效果研究

為了解決Textured crop的問題,作者黃承洧 這樣論述:

由Colletotrichum sp.造成的香蕉炭疽病是熱帶國家常見的採後病害,對熱帶、亞熱帶和溫帶地區的農作物造成重大經濟損失。銅和銀具有抗菌活性,被作為有效的抗菌劑,廣泛用於農業等領域中。金屬奈米粒子由於其尺寸小而展現出新的物理化學性質,具有更好的光學特性和抗菌活性,對微生物具有多種抗菌機制,而不只是農藥或抗生素單一特異性的機制,可用於防治多種病原菌,金屬奈米粒子或許可成為替代化學藥劑的抗菌成份之一。雷射去濕法製備奈米粒子具簡單、方便、快速、局部加熱、圖案化等優點。本研究使用高真空濺鍍系統沉積銅、銀、Cu50Ag50薄膜於玻璃基板上,使用NIR光纖脈衝雷射以不同的參數 (雷射功率、重複頻

率和掃描速度) 去濕薄膜以形成顆粒,不同膜厚 (50 nm、30 nm、10 nm) 的銅、銀薄膜:隨著膜厚降低,顆粒平均尺寸變小,尺寸達200 nm以下,有銅和銀的吸收峰出現。固定膜厚10 nm的薄膜:隨著增加雷射功率,製出的銅顆粒變小,吸收峰往藍移,且銅顆粒吸收峰值有變高的趨勢;隨著雷射功率的增加,銀顆粒尺寸則無明顯變化,吸收峰位置幾乎沒有改變,但吸收峰值有變高。探討平均脈衝能量對Cu50Ag50薄膜去濕後表面形貌的影響,較低的平均脈衝能量,具小米形/Cu40Ag60和大半球形/Cu20Ag80有兩種不同的奈米粒子,吸收光譜分別在約700 nm和500 nm處包含兩個峰;較高的平均脈衝能量

,奈米粒子具有一致的Cu40Ag60組成,平均直徑為100 nm,吸收光譜在約550 nm處出現吸收峰,因此推測奈米粒子中較高比例的銀導致光譜中吸收峰藍移,而小米形的奈米粒子導致吸收光峰紅移。隨著雷射去濕的累積能量密度 (AE) 增加,奈米粒子的尺寸減小,且皆具有線性關係:銅 (R2 = 0.88978)、Cu50Ag50 (R2 = 0.82681)、銀 (R2 = 0.8307),Cu50Ag50薄膜 (AE = 1.587 - 9.145 J/cm2) 比銅、銀薄膜 (AE = 1.587 - 3.139 J/cm2) 有更好的去濕表現。將不同尺寸之顆粒,與尺寸相近但成份組成不同之奈米粒

子,還有不同膜厚和成份組成之薄膜,用於評估對於香蕉炭疽病菌的抗菌效果。平板抑菌結果顯示:銅和銀皆具有良好的抗菌活性,隨著接觸的時間增加,抑菌率也跟著變高,銀的抗菌活性優於銅,能在更短的接觸時間下達到更高的抑菌率,薄膜和顆粒的抗菌率並沒有顯著差異。香蕉接種結果顯示:銅和銀皆具有良好抗菌活性,銀的抗菌活性優於銅,含銀的顆粒和薄膜皆能顯著降低病斑面積,銅顆粒比銅薄膜更能顯著降低病斑面積。純銅、純銀、銅銀合金之薄膜與顆粒皆顯著降低AlamarBlue還原率和造成分生孢子表面受損,推測抑制粒線體中酶的活性和對細胞壁/膜造成損傷為可能的抗菌機制。期待未來能實際應用於農業,提供一種防治香蕉炭疽病菌的新方法。