Titlebook: Artificial Intelligence; Second CAAI Internat Lu Fang,Daniel Povey,Ruiping Wang Conference proceedings 2022 The Editor(s) (if applicable) a

Sediment

书目名称Artificial Intelligence影响因子(影响力)




书目名称Artificial Intelligence影响因子(影响力)学科排名




书目名称Artificial Intelligence网络公开度




书目名称Artificial Intelligence网络公开度学科排名




书目名称Artificial Intelligence被引频次




书目名称Artificial Intelligence被引频次学科排名




书目名称Artificial Intelligence年度引用




书目名称Artificial Intelligence年度引用学科排名




书目名称Artificial Intelligence读者反馈




书目名称Artificial Intelligence读者反馈学科排名

Genome

Improving Adversarial Attacks with Ensemble-Based Approaches known models, meanwhile, keeping a higher success rate on all original models. In addition, the experiment result illustrates that, for more challenging targeted attacks, our methods exhibit higher transferability than other state-of-the-art attacks.

RENIN

旋转一周

An Optical Satellite Controller Based on Diffractive Deep Neural Networkconvert the light field at the output plane of DM module into electronic signals. Then, we trained the DM module to make the decoded electrical signals consistent with the desired optimal control commands. Therefore, when the light carrying input information and propagating through the well-trained

HARD

Incomplete Cigarette Code Recognition via Unified SPA Features and Graph Space Constraintsconstraints and calculate character spatial correlations and accurately estimates missing character landmarks. Finally, we employ the Hungarian algorithm to align recognition characters with estimated landmarks and fill missing characters with ‘*’ to preserve the complete semantic context, and produ

健忘症

ETH-TT: A Novel Approach for Detecting Ethereum Malicious Accountsas dataset for experiments. The results show that the ETH-TT method can achieve an F1-score of 95.4% with the cooperation of the XGBoost classifier, which is better than the detection method using only manual features.

Heart-Rate

Multi-objective Meta-return Reinforcement Learning for Sequential Recommendationnt effect (i.e., CTR), leading to trade-offs during optimization. To address these challenges, we propose a Multi-Objective Meta-return Reinforcement Learning (.) framework for sequential recommendation, which consists of a . and a .. Specifically, the . is designed to adaptively capture the return

种族被根除

Purchase Pattern Based Anti-Fraud Framework in Online E-Commerce Platform Using Graph Neural Networkveness of our framework, and the experimental results show that the DPP is able to capture more discriminative user patterns. Furthermore, GSR achieves the best performance compared to several state-of-the-art methods. Our method can be easily extended to other domains with the same problems as our

prediabetes

MIR

Blind Surveillance Image Quality Assessment via Deep Neural Network Combined with the Visual Saliencd thus have a great impact on the overall quality of the SIs. Next, the convolutional neural network (CNN) is adopted to extract quality-aware features for the whole image and local region, which are then mapped into the global and local quality scores through the fully connected (FC) network respec