Titlebook: Neural Information Processing; 29th International C Mohammad Tanveer,Sonali Agarwal,Adam Jatowt Conference proceedings 2023 The Editor(s) (

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書(shū)目名稱Neural Information Processing影響因子(影響力)




書(shū)目名稱Neural Information Processing影響因子(影響力)學(xué)科排名




書(shū)目名稱Neural Information Processing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Neural Information Processing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Neural Information Processing被引頻次




書(shū)目名稱Neural Information Processing被引頻次學(xué)科排名




書(shū)目名稱Neural Information Processing年度引用




書(shū)目名稱Neural Information Processing年度引用學(xué)科排名




書(shū)目名稱Neural Information Processing讀者反饋




書(shū)目名稱Neural Information Processing讀者反饋學(xué)科排名

galley

咯咯笑

Point Cloud Completion with?Difference-Aware Point Voting guidance of the geometric commonalities shared by the observed and missing parts. The decoder finally generates the new points that can be taken as the center points for generating missing regions. Quantitative and visual results on PCN and ShapeNet-55 datasets show that our model outperforms the s

inundate

聯(lián)邦

Local-Global Interaction and?Progressive Aggregation for?Video Salient Object Detectionaliency branch for elaborate interaction. In addition, PA evolves and aggregates RGB features, OF features and up-sampled features from the higher level, and can refine saliency-related features progressively. The sophisticated designs of interaction and aggregation phases effectively boost the perf

刻苦讀書(shū)

閹割

: Evading Ownership Detection Against Deep Learning Modelsry model which moves it decision boundary slightly. Our empirical results demonstrate that the adversary model evaded the DI detection with 40 samples. We also lay out the limitations of MEW and discuss them at last.

教義

標(biāo)準(zhǔn)

Combining Traffic Assignment and?Traffic Signal Control for?Online Traffic Flow Optimizationthe nearby road network. For traffic signal control, the Maximum Throughput Control (MTC) method is adopted. MTC checks the states of the intersections periodically and greedily takes the action that maximum the throughput of the intersections. By combining these two methods, the vehicle-road coordi

輕打

Frequency Spectrum with?Multi-head Attention for?Face Forgery Detectionrmed our experiments on smaller sets of DFFD dataset and tested on larger sets. The proposed model achieves an accuracy of 99%, having significantly fewer parameters in in-domain settings and thus is computationally less expensive. It is also tested on unseen datasets in cross GANs setting with an a