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

Sediment

書目名稱Artificial Intelligence影響因子(影響力)




書目名稱Artificial Intelligence影響因子(影響力)學(xué)科排名




書目名稱Artificial Intelligence網(wǎng)絡(luò)公開度




書目名稱Artificial Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Artificial Intelligence被引頻次




書目名稱Artificial Intelligence被引頻次學(xué)科排名




書目名稱Artificial Intelligence年度引用




書目名稱Artificial Intelligence年度引用學(xué)科排名




書目名稱Artificial Intelligence讀者反饋




書目名稱Artificial Intelligence讀者反饋學(xué)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

旋轉(zhuǎn)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

健忘癥

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

種族被根除

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