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On 2024年10月21日 上午10:57:35 [+0800], ncblab7041 朱彥煒:
  • Updated description of Rice disease hyperspectral image dataset(水稻病害高光譜影像資料集) from

    資料集為水稻病害影像資料集包含之資料主要為影像資料 (hdr檔)、標註資料 (xml檔) 。針對不同波長(470-900nm)進行感染水稻葉芽線蟲之種子影像蒐集。
    to
    # 水稻病害高光譜影像資料集 B150U 0034 說明文件 ## 1. 資料集概述 **B150U 0034.zip** 是一個針對水稻病害的高光譜影像資料集,資料集中的主要內容包括高光譜影像 (HDR 檔案) 與標註資料 (XML 檔案)。此資料集的目的是利用高光譜技術,針對波長範圍 **470 nm 至 900 nm** 的多個頻段進行感染水稻葉芽線蟲之種子的影像蒐集,並對病害進行標註。這些影像可用於分析病害發展的特徵,並支援病害預測模型的開發。 ## 2. 資料集內容 資料集包含以下主要檔案類型: - **高光譜影像檔 (RAW 檔案)**: - 每個檔案對應於不同波段下的水稻種子影像,這些影像捕捉了感染葉芽線蟲的種子在特定波長下的反射光譜信息。每個檔案均保存完整的光譜數據,包含可見光與近紅外波段(470 nm 到 900 nm),並依波長區分。 - **高光譜影像檔 (HDR 檔案)**: - 這是儲存raw檔裡面的詳細資料。 - **標註檔 (XML 檔案)**: - XML 檔案包含對影像中病害情況的標註信息,記錄了每個樣本的感染程度。標註的數據包括: - 種子是否被葉芽線蟲感染。 - 感染的嚴重程度,標註為輕度、中度或嚴重感染。 - **Meta數據檔 (metadata.csv)**: - 該檔案列出了每個樣本的詳細信息,包括樣本編號、拍攝時間、影像的波段範圍、影像拍攝條件以及感染標註等。 ## 3. 資料蒐集與處理流程 ### 3.1 影像蒐集 影像是透過高光譜相機在實驗室環境下進行拍攝,波長範圍從 **470 nm 到 900 nm**,涵蓋可見光與近紅外光譜。每張影像捕捉了特定波長下的種子反射光譜特徵,並針對水稻葉芽線蟲感染的不同情況進行蒐集,形成一個多維度的高光譜資料庫。 ### 3.2 標註資料 每個影像樣本根據種子是否受到葉芽線蟲感染,以及感染程度進行詳細標註: - **0**:未感染。 - **1**:輕度感染。 - **2**:中度感染。 - **3**:嚴重感染。 這些標註資料存放於 XML 檔案中,並以結構化方式儲存相關的標註信息,以便後續分析與模型訓練。 ### 3.3 高光譜數據處理 高光譜影像的每一個波段資料都需要進行校正與處理,以消除噪音與環境因素的影響。通常需要進行正規化與降噪處理,確保影像數據的準確性。後續可針對不同波段範圍的數據進行分析,以找出對於病害診斷最具代表性的波段。 ## 4. 資料應用場景 ### 4.1 病害預測模型訓練 本資料集可應用於機器學習或深度學習模型的訓練,尤其是在病害預測方面。研究人員可以利用高光譜影像的豐富數據,分析不同波段範圍內的光譜特徵,從而預測種子是否受到葉芽線蟲感染,並建立準確的病害預警系統。 ### 4.2 高光譜影像分析 透過分析不同波段範圍內的高光譜影像,可以進行水稻病害的早期診斷,並輔助研究人員深入理解葉芽線蟲感染的機制。這有助於開發病害預警系統,實現作物病害的自動檢測和實時監控。 ## 5. 使用方法 ### 5.1 資料使用要求 使用本資料集時,建議使用具備高光譜數據分析功能的工具進行資料處理,例如 Python 的 `spectral` 庫或其他常用的影像處理工具(如 `OpenCV` 和 `scikit-image`)。對於進行深度學習訓練的研究者,可以使用 TensorFlow 或 PyTorch 等框架來進行高光譜數據的預處理與模型訓練。 ### 5.2 資料預處理建議 - 在分析前,建議對高光譜影像進行正規化處理,以確保數據的統一性。 - 根據研究需求,可篩選出對病害診斷較為敏感的波段範圍進行特徵選取與模型訓練。 ## 6. 可能的研究發展方向 - **病害影像檢測模型開發**:可以基於高光譜影像數據開發專門的病害檢測模型,尤其是針對水稻葉芽線蟲感染的早期診斷,從而提高作物產量並減少病害損失。 - **波段範圍篩選與優化**:透過分析不同波段對病害特徵的影響,研究人員可以篩選出對病害檢測最具敏感度的波段,並進一步優化模型的準確性與效率。 ---


  • Changed value of field nchu_text_dataset_tag to 資料集為水稻病害影像資料集包含之資料主要為影像資料 (raw檔)、標註資料 (xml檔) 。針對不同波長(470-900nm)進行感染水稻葉芽線蟲之種子影像蒐集。 in Rice disease hyperspectral image dataset(水稻病害高光譜影像資料集)


  • Changed value of field nchu_textarea_dataset_annotation_mapping to <figure class="image"><img src="https://aidata.nchu.edu.tw/smarter/packages/20230314093537/messageImage_1729059337625.jpg"></figure> in Rice disease hyperspectral image dataset(水稻病害高光譜影像資料集)


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"\u8cc7\u6599\u96c6\u8aaa\u660e\u7121\u5c0d\u5176\u4ed6\u8cc7\u6599\u5f15\u7528"}, {"cat": "Findable", "serial": "RDA-F4-01M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u53ef\u4ee5\u88ab\u6536\u96c6\u548c\u7d22\u5f15", "eval_desc": "*\u8cc7\u6599\u96c6\u4e0a\u67b6\u5e73\u53f0\u5f8c\u5373\u7b26\u5408\u6b64\u9805\u6e96\u5247", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u9801\u9762\u53ef\u88ab\u700f\u89bd\u5668\u627e\u5230\u3002\u4f8b\u5982: \u5728\u8a08\u756b\u6240\u81ea\u5efa\u7684\u5171\u4eab\u5e73\u53f0\u4e0a\u6709\u63d0\u4f9b\u67e5\u8a62\u4ecb\u9762\u4ee5\u627e\u5230\u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u9801\u9762\u6216\u8cc7\u6599\u96c6\u8aaa\u660e\u6587\u4ef6\u3002", "answer": "\u5be6\u65bd\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u6587\u4ef6\u5305\u542b\u4f7f\u7528\u8005\u80fd\u5920\u53d6\u7528\u7684\u8cc7\u8a0a"}, {"cat": "Accessible", "serial": "RDA-A1-04D", "eval": "\u900f\u904e\u6a19\u6e96\u5316\u5354\u5b9a\u53d6\u7528\u8cc7\u6599", "eval_desc": "*\u8cc7\u6599\u96c6\u4e0a\u67b6\u5e73\u53f0\u5f8c\u5373\u7b26\u5408\u6b64\u9805\u6e96\u5247", "eval_prompt": "\u4f8b\u5982\uff1a\u53d6\u7528\u5354\u5b9a\u662f HTTP \u6216FTP\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u53d6\u7528\u5354\u5b9a\u662fFTP"}, {"cat": "Reusable", "serial": "RDA-R1.3-01M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u7b26\u5408\u793e\u7fa4\u6a19\u6e96", "eval_desc": "[\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5]\u8a6e\u91cb\u8cc7\u6599\u7b26\u5408\u793e\u7fa4\u6a19\u6e96", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u6587\u4ef6\u7684\u683c\u5f0f\u7b26\u5408\u793e\u7fa4\u6a19\u6e96\uff0c\u4f8b\u5982\u8a72\u8a6e\u91cb\u8cc7\u6599\u6a19\u6e96\u5df2\u6536\u9304\u5728\u8a3b\u518a\u8868\u4e2d(\u5982 FAIRsharing \u6240\u958b\u767c\u7684)\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5\u8a6e\u91cb\u8cc7\u6599\u8aaa\u660e\u7b26\u5408\u793e\u7fa4\u6a19\u6e96\uff0c\u5177\u6a5f\u5668\u53ef\u7406\u89e3\u8868\u9054\u683c\u5f0f"}, {"cat": "Interoperable", "serial": "RDA-I3-01D", "eval": "\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u5f15\u7528", "eval_desc": "[\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5]\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u5f15\u7528", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u6587\u4ef6\u4e2d\u6709\u63d0\u5230\u8cc7\u6599\u96c6\u6709\u5f15\u7528\u5230\u5176\u4ed6\u8cc7\u6599\u3002\u4f8b\u5982: \u8cc7\u6599\u96c6\u5b58\u5728\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u5f15\u7528\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u8aaa\u660e\u7121\u5c0d\u5176\u4ed6\u8cc7\u6599\u5f15\u7528"}, {"cat": "Reusable", "serial": "RDA-R1.3-01D", "eval": "\u8cc7\u6599\u7b26\u5408\u793e\u7fa4\u6a19\u6e96", "eval_desc": "[\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5]\u8cc7\u6599\u7b26\u5408\u793e\u7fa4\u6a19\u6e96", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8cc7\u6599\u6a21\u578b\u8207\u683c\u5f0f\u7b26\u5408\u793e\u7fa4\u6a19\u6e96\uff0c\u4f8b\u5982\u8a72\u8cc7\u6599\u6a21\u578b\u8207\u683c\u5f0f\u4e4b\u6a19\u6e96\u5df2\u6536\u9304\u5728\u8a3b\u518a\u8868\u4e2d(\u5982 FAIRsharing \u6240\u958b\u767c\u7684)\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5\u8a6e\u91cb\u8cc7\u6599\u8aaa\u660e\u7b26\u5408\u793e\u7fa4\u6a19\u6e96\uff0c\u5177\u6a5f\u5668\u53ef\u7406\u89e3\u8868\u9054\u683c\u5f0f"}, {"cat": "Accessible", "serial": "RDA-A1-05D", "eval": "\u53ef\u4ee5\u81ea\u52d5\u5316\u53d6\u7528\u8cc7\u6599(\u5373\u900f\u904e\u8a08\u7b97\u6a5f\u7a0b\u5e8f)", "eval_desc": "*\u8cc7\u6599\u96c6\u4e0a\u67b6\u5e73\u53f0\u5f8c\u5373\u7b26\u5408\u6b64\u9805\u6e96\u5247(\u5177API)", "eval_prompt": "\u4f8b\u5982\uff1a\u53ef\u900f\u904e https://purl.org/\u8cc7\u6599\u96c6PURL\u8b58\u5225\u7b26\uff0c\u81ea\u52d5\u53d6\u7528\u8a72PURL\u8b58\u5225\u7b26\u6240\u4ee3\u8868\u7684\u8cc7\u6599\u96c6\u4e4b\u8cc7\u6599\u3002\u4f8b\u5982\uff1a\u53ef\u900f\u904eAPI\u81ea\u52d5\u53d6\u5f97\u8cc7\u6599\u96c6\u4e4b\u8cc7\u6599\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8b58\u5225\u8cc7\u6599\u7533\u8acb\u4e2d"}, {"cat": "Interoperable", "serial": "RDA-I3-02M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u5f15\u7528", "eval_desc": "[\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5]\u8a6e\u91cb\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u5f15\u7528", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u6587\u4ef6\u4e2d\u63d0\u5230\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u5f15\u7528\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u8aaa\u660e\u7121\u5c0d\u5176\u4ed6\u8cc7\u6599\u5f15\u7528"}, {"cat": "Accessible", "serial": "RDA-A1.1-01M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u53ef\u7d93\u7531\u514d\u8cbb\u53d6\u7528\u5354\u5b9a\u53d6\u7528", "eval_desc": "*\u8cc7\u6599\u96c6\u4e0a\u67b6\u5e73\u53f0\u5f8c\u5373\u7b26\u5408\u6b64\u9805\u6e96\u5247", "eval_prompt": "\u4f8b\u5982\uff1a\u53d6\u7528\u5354\u5b9a\u662f HTTP \u6216FTP\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u53d6\u7528\u5354\u5b9a\u662fFTP"}, {"cat": "Reusable", "serial": "RDA-R1.3-02M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u4ee5\u7b26\u5408\u6a5f\u5668\u53ef\u7406\u89e3\u7684\u793e\u7fa4\u6a19\u6e96\u4f86\u8868\u793a", "eval_desc": "\u67e5\u8b49\u8a6e\u91cb\u8cc7\u6599\u63a1\u7528\u7684\u793e\u7fa4\u6a19\u6e96\u662f\u5177\u6709\u6a5f\u5668\u53ef\u7406\u89e3\u7684\u8868\u9054\u5f0f(\u82e5\u7121\u6cd5\u78ba\u5b9a\u662f\u5426\u7b26\u5408\u6b64\u9805\u8981\u6c42\u5247\u52fe\u9078[\u5c1a\u672a\u8003\u616e])", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8a6e\u91cb\u8cc7\u6599\u7684\u683c\u5f0f\u7b26\u5408\u793e\u7fa4\u6a19\u6e96\uff0c\u5177\u6709\u6a5f\u5668\u53ef\u7406\u89e3\u7684\u8868\u9054\u5f0f\u3002", "answer": "\u5c1a\u672a\u8003\u616e", "note": "\u5c1a\u672a\u8003\u616e"}, {"cat": "Accessible", "serial": "RDA-A1.1-01D", "eval": "\u8cc7\u6599\u53ef\u7d93\u7531\u514d\u8cbb\u53d6\u7528\u5354\u5b9a\u53d6\u7528", "eval_desc": "*\u8cc7\u6599\u96c6\u4e0a\u67b6\u5e73\u53f0\u5f8c\u5373\u7b26\u5408\u6b64\u9805\u6e96\u5247", "eval_prompt": "\u4f8b\u5982\uff1a\u53d6\u7528\u5354\u5b9a\u662f HTTP \u6216FTP\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u53d6\u7528\u5354\u5b9a\u662fFTP"}, {"cat": "Interoperable", "serial": "RDA-I3-02D", "eval": "\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u9650\u5b9a\u5f15\u7528", "eval_desc": "[\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5]\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u9650\u5b9a\u5f15\u7528", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u6587\u4ef6\u4e2d\u6709\u63d0\u5230\u8cc7\u6599\u96c6\u6709\u5f15\u7528\u5230\u5176\u4ed6\u8cc7\u6599\uff0c\u4e14\u5df2\u8aaa\u660e\u6b64\u5f15\u7528\u548c\u6b64\u8cc7\u6599\u96c6\u7684\u95dc\u4fc2\u3002\u4f8b\u5982: \u8cc7\u6599\u96c6\u5b58\u5728\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u9650\u5b9a\u5f15\u7528\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u8aaa\u660e\u7121\u5c0d\u5176\u4ed6\u8cc7\u6599\u5f15\u7528"}, {"cat": "Reusable", "serial": "RDA-R1.3-02D", "eval": "\u8cc7\u6599\u4ee5\u7b26\u5408\u6a5f\u5668\u53ef\u7406\u89e3\u7684\u793e\u7fa4\u6a19\u6e96\u4f86\u8868\u793a", "eval_desc": "\u67e5\u8b49\u8cc7\u6599\u63a1\u7528\u7684\u793e\u7fa4\u6a19\u6e96\u662f\u5177\u6709\u6a5f\u5668\u53ef\u7406\u89e3\u7684\u8868\u9054\u5f0f(\u82e5\u7121\u6cd5\u78ba\u5b9a\u662f\u5426\u7b26\u5408\u6b64\u9805\u8981\u6c42\u5247\u52fe\u9078[\u5c1a\u672a\u8003\u616e])", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8cc7\u6599\u6a21\u578b\u8207\u683c\u5f0f\u7b26\u5408\u793e\u7fa4\u6a19\u6e96\uff0c\u5177\u6709\u6a5f\u5668\u53ef\u7406\u89e3\u7684\u8868\u9054\u5f0f\u3002", "answer": "\u5c1a\u672a\u8003\u616e", "note": "\u5c1a\u672a\u8003\u616e"}, {"cat": "Interoperable", "serial": "RDA-I3-03M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8a6e\u91cb\u8cc7\u6599\u7684\u9650\u5b9a\u5f15\u7528", "eval_desc": "[\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5]\u8a6e\u91cb\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8a6e\u91cb\u8cc7\u6599\u7684\u9650\u5b9a\u5f15\u7528", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u6587\u4ef6\u4e2d\u63d0\u5230\u5c0d\u5176\u4ed6\u8a6e\u91cb\u8cc7\u6599\u7684\u5f15\u7528\uff0c\u4e14\u5df2\u8aaa\u660e\u6b64\u5f15\u7528\u548c\u6b64\u8cc7\u6599\u96c6\u7684\u95dc\u4fc2\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u8aaa\u660e\u7121\u5c0d\u5176\u4ed6\u8cc7\u6599\u5f15\u7528"}, {"cat": "Accessible", "serial": "RDA-A1.2-01D", "eval": "\u8cc7\u6599\u53ef\u7d93\u7531\u652f\u6301\u8eab\u4efd\u9a57\u8b49\u548c\u6388\u6b0a\u53d6\u7528\u5354\u5b9a\u53d6\u7528", "eval_desc": "*\u8cc7\u6599\u96c6\u4e0a\u67b6\u5e73\u53f0\u5f8c\u5373\u7b26\u5408\u6b64\u9805\u6e96\u5247", "eval_prompt": "\u4f8b\u5982\uff1a\u53d6\u7528\u8cc7\u6599\u96c6\u524d\u9700\u8981\u5148\u767b\u5165\u5e33\u865f\u3002", "answer": "\u5be6\u65bd\u968e\u6bb5", "note": "\u7533\u8acb\u524d\u9808\u767b\u5165\u5e33\u865f"}, {"cat": "Accessible", "serial": "RDA-A2-01M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u4fdd\u8b49\u5728\u8cc7\u6599\u4e0d\u518d\u53ef\u7528\u5f8c\u4ecd\u7136\u53ef\u7528", "eval_desc": "*\u8cc7\u6599\u96c6\u4e0a\u67b6\u5e73\u53f0\u5f8c\u5373\u7b26\u5408\u6b64\u9805\u6e96\u5247", "eval_prompt": "\u4f8b\u5982\uff1a\u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u9801\u9762\u6709\u8aaa\u660e\u5982\u679c\u8cc7\u6599\u96c6\u4e0d\u518d\u53ef\u7528\uff0c\u6b64\u8aaa\u660e\u7db2\u9801\u5c07\u4ecd\u7136\u5b58\u5728\u3002", "answer": "\u5be6\u65bd\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u8aaa\u660e\u7db2\u9801\u4ecd\u7136\u5b58\u5728"}, {"cat": "Interoperable", "serial": "RDA-I3-04M", "eval": "\u8a6e\u91cb\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u9650\u5b9a\u5f15\u7528", "eval_desc": "[\u8cc7\u6599\u96c6\u4e0a\u67b6\u524d\u5be9\u67e5]\u8a6e\u91cb\u8cc7\u6599\u5167\u542b\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u9650\u5b9a\u5f15\u7528", "eval_prompt": "\u4f8b\u5982: \u8cc7\u6599\u96c6\u7684\u8aaa\u660e\u6587\u4ef6\u4e2d\u63d0\u5230\u5c0d\u5176\u4ed6\u8cc7\u6599\u7684\u5f15\u7528\uff0c\u4e14\u5df2\u8aaa\u660e\u6b64\u5f15\u7528\u548c\u6b64\u8cc7\u6599\u96c6\u7684\u95dc\u4fc2\u3002", "answer": "\u898f\u5283\u968e\u6bb5", "note": "\u8cc7\u6599\u96c6\u8aaa\u660e\u7121\u5c0d\u5176\u4ed6\u8cc7\u6599\u5f15\u7528"}] in Rice disease hyperspectral image dataset(水稻病害高光譜影像資料集)