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Box with inlaid gold and silver cloud patterns
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作者 De-rui Tan 《China Foundry》 SCIE 2019年第5期I0002-I0003,共2页
The late Warring States Period (475 B.C-221 B.C)Caliber diameter:18.2 cm Bronze with inlaid silver The surfaces of the utensil body and the lid are decorated with cloud patterns by using the inlaid gold or silver fila... The late Warring States Period (475 B.C-221 B.C)Caliber diameter:18.2 cm Bronze with inlaid silver The surfaces of the utensil body and the lid are decorated with cloud patterns by using the inlaid gold or silver filaments and flakes. The decorative patterns are very slim and extremely exquisite. 展开更多
关键词 Box with inlaid gold and silver cloud patterns
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Deep Learning Framework for Precipitation Prediction Using Cloud Images
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作者 Mirza Adnan Baig Ghulam Ali Mallah Noor Ahmed Shaikh 《Computers, Materials & Continua》 SCIE EI 2022年第8期4201-4213,共13页
Precipitation prediction(PP)have become one of the significant research areas of deep learning(DL)and machine vision(MV)techniques are frequently used to predict the weather variables(WV).Since the climate change has ... Precipitation prediction(PP)have become one of the significant research areas of deep learning(DL)and machine vision(MV)techniques are frequently used to predict the weather variables(WV).Since the climate change has left significant impact upon weather variables(WV)and continuously changes are observed in temperature,humidity,cloud patterns and other factors.Although cloud images contain sufficient information to predict the precipitation pattern but due to changes in climate,the complex cloud patterns and rapid shape changing behavior of clouds are difficult to consider for rainfall prediction.Prediction of rainfall would provide more meticulous assistance to the farmers to know about the weather conditions and to care their cash crops.This research proposes a framework to classify the dark cloud patterns(DCP)for prediction of precipitation.The framework consists upon three steps to classify the cloud images,first step tackles noise reduction operations,feature selection and preparation of datasets.Second step construct the decision model by using convolutional neural network(CNN)and third step presents the performance visualization by using confusion matrix,precision,recall and accuracy measures.This research contributes(1)real-world clouds datasets(2)method to prepare datasets(3)highest classification accuracy to predict estimated as 96.90%. 展开更多
关键词 Machine vision SIFT features dark cloud patterns PRECIPITATION AGRICULTURE
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