Titlebook: Digital Interaction and Machine Intelligence; Proceedings of MIDI’ Cezary Biele,Janusz Kacprzyk,Marcin Sikorski Conference proceedings 2021

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書目名稱Digital Interaction and Machine Intelligence影響因子(影響力)




書目名稱Digital Interaction and Machine Intelligence影響因子(影響力)學(xué)科排名




書目名稱Digital Interaction and Machine Intelligence網(wǎng)絡(luò)公開度




書目名稱Digital Interaction and Machine Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Digital Interaction and Machine Intelligence被引頻次




書目名稱Digital Interaction and Machine Intelligence被引頻次學(xué)科排名




書目名稱Digital Interaction and Machine Intelligence年度引用




書目名稱Digital Interaction and Machine Intelligence年度引用學(xué)科排名




書目名稱Digital Interaction and Machine Intelligence讀者反饋




書目名稱Digital Interaction and Machine Intelligence讀者反饋學(xué)科排名

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描繪

Lecture Notes in Computer Scienceold cross-validation process on the dataset and found that the trained Neural Networks model gives the best mean accuracy (96%) in detecting similarity between two text bodies. We demonstrated that our proposed method outperforms results gained from individual character-based similarity measurement.

Hay-Fever

Risk Assessment and Risk-Driven Testingst YOLO Version-3 Convolutional Neural Network object detector for detecting palm-trees in drone images captured in a desert area that includes palm-trees of different sizes, resolution, ground spread, degree of overlap, etc. In particular, we discuss the specific training strategy adopted and hyper

GENRE

FISC

FISC

malapropism

P. H. M. Lohman,A. J. van der Ebput image. For performance evaluation, a subset of 220 images from six surveillance datasets has been used, consisting of individuals with varying distances from the camera, changing illumination conditions, and complex backgrounds. The performance of these algorithms has been evaluated and compared

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