Titlebook: Intelligent Systems; 12th Brazilian Confe Murilo C. Naldi,Reinaldo A. C. Bianchi Conference proceedings 2023 The Editor(s) (if applicable)

語言學(xué)

Deep Reinforcement Learning for?Voltage Control in?Power Systemsoach, three novel reinforcement learning variations named windowed, ensemble and windowed ensemble Q-Learning, which alter the agent’s learning process for voltage control, are presented and tested on IEEE 13, 37 and 123 bus systems, simulated on OpenDSS.

束以馬具

Femine

Evaluating Recent Legal Rhetorical Role Labeling Approaches Supported by?Transformer Encoders on data augmentation and positional encoders do not provide performance gains to our models. Conversely, the models based on the DFCSC approach overcome the appropriate baselines, and they do remarkably well as the lowest and highest improvements respectively are 5.9% and 10.4%.

fulcrum

Dog Face Recognition Using Vision Transformerelationships between them. Results obtained on DogFaceNet, a public database of dog face images, show that the proposed method, which uses the EfficientFormer-L1 architecture, outperforms the state-of-the-art method proposed previously in literature based on ResNet, a deep convolutional neural network.

Arresting

輕快走過

EfficientDeepLab for?Automated Trachea Segmentation on?Medical Imagesmatic segmentation methodologies can speed up organ delimiting during radiotherapy planning. This work designs a method, EfficientDeepLab, a convolutional neural network architecture trained on CT scans for trachea segmentation, and obtained an 88.6% dice score.

換話題

直覺好

Onerous

不連貫