Titlebook: Vom Wesen der deutschen Universit?t; René K?nig Book 20001st edition Springer Fachmedien Wiesbaden 2000 Bildung.Denker, deutsche.Fichte.Hu

Callow

書目名稱Vom Wesen der deutschen Universit?t影響因子(影響力)




書目名稱Vom Wesen der deutschen Universit?t影響因子(影響力)學(xué)科排名




書目名稱Vom Wesen der deutschen Universit?t網(wǎng)絡(luò)公開度




書目名稱Vom Wesen der deutschen Universit?t網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Vom Wesen der deutschen Universit?t被引頻次




書目名稱Vom Wesen der deutschen Universit?t被引頻次學(xué)科排名




書目名稱Vom Wesen der deutschen Universit?t年度引用




書目名稱Vom Wesen der deutschen Universit?t年度引用學(xué)科排名




書目名稱Vom Wesen der deutschen Universit?t讀者反饋




書目名稱Vom Wesen der deutschen Universit?t讀者反饋學(xué)科排名

爭吵

aze behavior correlates to the type of the action under execution. This information is then used to plan the leader’s actions in order to sustain the leader/follower alignment in the social interaction..The model of the leader’s gaze behavior and the alignment of the intentions is evaluated in a hum

CRUC

René K?nig network. By combining both modalities, we build a pipeline that learns to super-resolve using multi-scale spectral inputs guided by a color image. Finally, we validate our method and show that it is economic in terms of parameters and computation time, while still producing state-of-the-art results

GEST

assent

Esophagus

struction, which is beneficial to the structured prediction of the target images. Further more, we implement adversarial training at the output space of the segmentation network to align the structured prediction of the source and target images based on the similar spatial structure they share. To v

吵鬧

René K?nigon popular benchmarks. Our extensive experimentation shows that the proposed weighted aggregation with enhancement filter (WAEF) tracker outperforms the baseline (ECO) in almost all the challenging categories on OTB50 dataset with a cumulative gain of 14.8%. As per the VOT2016 evaluation, the propos

Arthropathy

René K?nigead of using previously generated results, our decoder utilizes a reference hand pose to provide equivalent dependencies among hand joints for each output joint generation. By imposing the reference structural dependencies, we can correlate the information with the input 3D points through a multi-he

聽寫

Water-Brash