Titlebook: Artificial Intelligence and Mobile Services – AIMS 2022; 11th International C Xiuqin Pan,Ting Jin,Liang-Jie Zhang Conference proceedings 20

連鎖

Indicator-Specific Recurrent Neural Networks with?Co-teaching for?Stock Trend Predictiond prediction and achieve impressive results. However, these methods still suffer from two limitations: 1) Various types of technical indicators are input into a single model, making it difficult for the model to learn differentiated features. 2) Noisy data in the stocks is not handled effectively. T

忍耐

SATMeas - Object Detection and Measurement: Canny Edge Detection Algorithmhouses, courier companies, airport containers at airports etc. cannot always get precise/accurate measurement using human hands. In our research we have developed an application SATMeas to detect the object and give the measurements of the object in real-time. We have utilized the canny edge detecti

柔美流暢

Multi-Classification of Electric Power Metadata based on Prompt-tuning, meteorology, satellites, etc. These industrial data are rich in value, and will be the foundation of digital economy and information management. Due to the particularity of the industry, the exploitation of big data mainly faces the following challenges that degrade the performance of mainstream g

紀(jì)念

Dual-Branch Network Fused with Attention Mechanism for Clothes-Changing Person Re-identificationcs of people, such as gait and body shape. Most of the current methods assume that persons’ clothes will not change in a short period of time, so these methods are not applicable when changing clothes. Based on this situation, this paper proposes a dual-branch network clothes-changing person re-iden

極肥胖

Infant Cry Classification Based-On Feature Fusion and Mel-Spectrogram Decomposition with CNNsom transfer learning convolutional neural network model and mel-spectrogram features extracted from mel-spectrogram decomposition model are fused and fed into a multiple layer perception for better classification accuracy. The mel-spectrogram decomposition method feeds band-wise crops of the mel-spe

NATAL

commute

https://doi.org/10.1007/978-3-030-53051-8 to each other, which leads to the broadcast storm effect on the network. Therefore, this paper proposes a Fuzzy logic-based scheme to mitigate the broadcast storm effect. The novelty of this paper is the suggestion and application of a Fuzzy logic approach in order to mitigate critical data broadca

commodity

Gesetz über elektronische Wertpapiere (eWpG) achieves 45% and 42% UAR?(Unweighted Average Recall), on the development dataset. After model fusion, DCRNNX achieves 46.89% UAR and 37.0% UAR on development and test datasets, respectively. The performance of our method on the development dataset is nearly 6% better than the baselines. Especially,

Angioplasty

Gesetz über elektronische Wertpapiere (eWpG)above two parts. Besides, since translation can not be incorporated into the bilinear model directly, we introduce translation matrix as the equivalent. Theoretical analysis proves that STaR is capable of modeling all patterns and handling complex relations simultaneously, and experiments demonstrat

Diastole

Christian Conreder,Johannes Meierr to integrate both of the two-level vector representations. Experimental results on two datasets demonstrate that our proposed method outperforms the baseline methods over 1.38–21.82% and 3.42–20.7% in terms of relative F1-measure on two Chinese text classification benchmarks, respectively.