Titlebook: Industrial Crystallization; Process Simulation A Narayan S. Tavare Book 1995 Springer Science+Business Media New York 1995 crystal.crystall

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書(shū)目名稱Industrial Crystallization影響因子(影響力)




書(shū)目名稱Industrial Crystallization影響因子(影響力)學(xué)科排名




書(shū)目名稱Industrial Crystallization網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Industrial Crystallization網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Industrial Crystallization被引頻次




書(shū)目名稱Industrial Crystallization被引頻次學(xué)科排名




書(shū)目名稱Industrial Crystallization年度引用




書(shū)目名稱Industrial Crystallization年度引用學(xué)科排名




書(shū)目名稱Industrial Crystallization讀者反饋




書(shū)目名稱Industrial Crystallization讀者反饋學(xué)科排名

男生如果明白

Narayan S. Tavarecrease the quality of real-world low-resolution images. We have applied the proposed pipeline for the problem of face super-resolution where we report large improvement over baselines and prior work although the proposed method is potentially applicable to other object categories.

grotto

Narayan S. Tavarecessing of RGB-D data with . includes noise and temporal flickering removal, hole filling and resampling. As a substitute of the observed scene, our . can additionally be applied to compression and scene reconstruction. We present experiments performed with our framework in indoor scenes of differen

拾落穗

營(yíng)養(yǎng)

Narayan S. Tavare joint locations to estimate a sequence of 3D poses. We designed a sequence-to-sequence network composed of layer-normalized LSTM units with shortcut connections connecting the input to the output on the decoder side and imposed temporal smoothness constraint during training. We found that the knowl

CHAR

Goblet-Cells

Narayan S. Tavareize the elements of the feature pool to a uniform size and aggregate their contextual information to generate each level of the final FP. The experimental results confirmed that PFPNet increases the performance of the latest version of the single-shot multi-box detector (SSD) by mAP of 6.4% AP and e

LAITY

Dawdle

Narayan S. Tavare TPN with bi-directional training on pairs of frames. We apply the switchable TPN to three tasks: colorizing a gray-scale video based on a few colored key-frames, generating an HDR video from a low dynamic range (LDR) video and a few HDR frames, and propagating a segmentation mask from the first fra

泥瓦匠

Narayan S. Tavareproposed to predict the labels of unlabeled image sequences. With the newly estimated labeled sequences, the unified anchor embedding framework enables the feature learning process to be further facilitated. Extensive experimental results on the large-scale dataset show that the proposed method outp