變更
On 2022年8月30日 下午12:04:28 [+0800], 王健合:
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Updated description of 水稻產量預測模型 from
藉由獲得稻米多光譜影像資料,與其所計算出的多個指標數值,建立一套深度學習系統,完成預測未知的水稻產量
to藉由輸入水稻多光譜影像資料,完成產量的預測
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新增下列標籤至 水稻產量預測模型
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Changed value of field
nchu_texarea_dataset_value
to確保水稻的產量,提高農民的收益
in 水稻產量預測模型 -
Changed value of field
nchu_texarea_dataset_usage
to隨著準確率的提升,可以縮短空拍機人員的拍攝天數,使其具有經濟效益,並提前預測出產量,以調整種植管理(ex:施肥,灌溉)
in 水稻產量預測模型 -
Changed value of field
nchu_texarea_dataset_purpose
to使用水稻種植後11個時間點空拍機取得的多光譜影像資料進行最終產量的預測
in 水稻產量預測模型 -
Changed value of field
nchu_text_dataset_source
to改作
in 水稻產量預測模型 -
Changed value of field
nchu_ddl_dataset_type
to[]
in 水稻產量預測模型 -
Changed value of field
nchu_ddl_dataset_update_frequency
to不定期
in 水稻產量預測模型
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45 | "nchu_text_dataset_maintainer_email": "d108056006@mail.nchu.edu.tw", | 43 | "nchu_text_dataset_maintainer_email": "d108056006@mail.nchu.edu.tw", | ||
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52 | "nchu_text_dataset_name_org_eng_shortname": "01", | 50 | "nchu_text_dataset_name_org_eng_shortname": "01", | ||
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54 | "nchu_text_dataset_name_yyyymmdd": "20220829", | 52 | "nchu_text_dataset_name_yyyymmdd": "20220829", | ||
55 | "nchu_text_dataset_performance_capacity": "", | 53 | "nchu_text_dataset_performance_capacity": "", | ||
56 | "nchu_text_dataset_performance_cpu_model": "", | 54 | "nchu_text_dataset_performance_cpu_model": "", | ||
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70 | "nchu_text_dataset_performance_result_type": "", | 68 | "nchu_text_dataset_performance_result_type": "", | ||
71 | "nchu_text_dataset_provider_email": "d108056006@mail.nchu.edu.tw", | 69 | "nchu_text_dataset_provider_email": "d108056006@mail.nchu.edu.tw", | ||
72 | "nchu_text_dataset_provider_name": "\u738b\u5065\u5408", | 70 | "nchu_text_dataset_provider_name": "\u738b\u5065\u5408", | ||
73 | "nchu_text_dataset_provider_tel": "0981136858", | 71 | "nchu_text_dataset_provider_tel": "0981136858", | ||
74 | "nchu_text_dataset_serial": "20220829183022", | 72 | "nchu_text_dataset_serial": "20220829183022", | ||
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76 | "nchu_text_dataset_title_eng": "rice_yield_prediction_model", | 74 | "nchu_text_dataset_title_eng": "rice_yield_prediction_model", | ||
77 | "nchu_text_dataset_training_capacity": "", | 75 | "nchu_text_dataset_training_capacity": "", | ||
78 | "nchu_text_dataset_training_cpu_model": "", | 76 | "nchu_text_dataset_training_cpu_model": "", | ||
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110 | "notes": | 108 | "notes": | ||
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114 | "organization": { | 112 | "organization": { | ||
115 | "approval_status": "approved", | 113 | "approval_status": "approved", | ||
116 | "created": "2022-05-19T11:00:07.149574", | 114 | "created": "2022-05-19T11:00:07.149574", | ||
117 | "description": "1234rterwe4reretesrw", | 115 | "description": "1234rterwe4reretesrw", | ||
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170 | "toolinfos": "[]", | 182 | "toolinfos": "[]", | ||
171 | "type": "dataset", | 183 | "type": "dataset", | ||
172 | "url": null, | 184 | "url": null, | ||
173 | "version": null | 185 | "version": null | ||
174 | } | 186 | } |