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Found 10 papers, 3 papers with code
Network-Constrained Unit Commitment with Flexible Temporal Resolution
Modern network-constrained unit commitment (NCUC) bears a heavy computational burden due to the ever-growing model scale.
SSHNN: Semi-Supervised Hybrid NAS Network for Echocardiographic Image Segmentation
Compared with manual design, Neural Architecture Search (NAS) realizes better segmentation results due to larger search space and automatic optimization, but most of the existing methods are weak in layer-wise feature aggregation and adopt a ``strong encoder, weak decoder" structure, insufficient to handle global relationships and local details.
Registration-Free Hybrid Learning Empowers Simple Multimodal Imaging System for High-quality Fusion Detection
Multimodal fusion detection always places high demands on the imaging system and image pre-processing, while either a high-quality pre-registration system or image registration processing is costly.
Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review
For invasive breast cancer, immunohistochemical (IHC) techniques are often used to detect the expression level of human epidermal growth factor receptor-2 (HER2) in breast tissue to formulate a precise treatment plan.
Look-Ahead AC Optimal Power Flow: A Model-Informed Reinforcement Learning Approach
With the increasing proportion of renewable energy in the generation side, it becomes more difficult to accurately predict the power generation and adapt to the large deviations between the optimal dispatch scheme and the day-ahead scheduling in the process of real-time dispatch.
Evaluation of Look-ahead Economic Dispatch Using Reinforcement Learning
In this paper, we propose an evaluation approach to analyze the performance of RL agents in a look-ahead economic dispatch scheme.
Open-Access Data and Toolbox for Tracking COVID-19 Impact on Power Systems
Intervention policies against COVID-19 have caused large-scale disruptions globally, and led to a series of pattern changes in the power system operation.
Construct Informative Triplet with Two-stage Hard-sample Generation
In this paper, we propose a robust sample generation scheme to construct informative triplets.
PML: Progressive Margin Loss for Long-tailed Age Classification
In this paper, we propose a progressive margin loss (PML) approach for unconstrained facial age classification.
A New Deep Neural Architecture Search Pipeline for Face Recognition
In this paper, we first propose a new deep neural architecture search pipeline combined with NAS technology and reinforcement learning strategy into face recognition.
