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Found 5 papers, 1 papers with code
Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNN
In the past decade, convolutional neural networks (CNNs) have shown prominence for semantic segmentation.
Optimal Operation of a Hydrogen-based Building Multi-Energy System Based on Deep Reinforcement Learning
To overcome the challenge, we reformulate the problem as a Markov game and propose an energy management algorithm to solve it based on multi-agent discrete actor-critic with rules (MADACR).
MSCFNet: A Lightweight Network With Multi-Scale Context Fusion for Real-Time Semantic Segmentation
In recent years, how to strike a good trade-off between accuracy and inference speed has become the core issue for real-time semantic segmentation applications, which plays a vital role in real-world scenarios such as autonomous driving systems and drones.
Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings
In this paper, we intend to minimize the energy cost of an HVAC system in a multi-zone commercial building under dynamic pricing with the consideration of random zone occupancy, thermal comfort, and indoor air quality comfort.
Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning
In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD^2L) approach for SR person re-identification.
