FORKNET: STRONG SEMANTIC FEATURE REPRESENTATION AND SUBREGION SUPERVISION FOR ACCURATE REMOTE SENSING CHANGE DETECTION

ForkNet: Strong Semantic Feature Representation and Subregion Supervision for Accurate Remote Sensing Change Detection

In this article, we propose an effective siamese feature pyramid network (FPN), ForkNet, for remote sensing change detection (RSCD).We find that the siamese network structure, which is widely used for RSCD, contains click here only one downsampling network in the feature extraction stage, e.g., VGG16 and ResNet-18, to extract the deep features of a

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Solving Action Semantic Conflict in Physically Heterogeneous Multi-Agent Reinforcement Learning with Generalized Action-Prediction Optimization

Traditional multi-agent reinforcement learning (MARL) algorithms typically implement global parameter sharing across various types of heterogeneous agents without meticulously differentiating between different action semantics.This approach results in the action semantic conflict problem, which decreases the generalization ability of policy network

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