Tag: deep learning
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CANGuard: Hybrid CNN-GRU Model for CAN Bus Intrusion Detection
CANGuard uses a hybrid CNN-GRU-attention model to detect intrusions in in-vehicle CAN networks, enhancing security in smart transportation systems.
Hamiltonian Dynamics and Bottleneck in Leaky ResNets
Explore Hamiltonian mechanics in Leaky ResNets revealing bottleneck structures and adaptive training for improved feature learning and efficiency.
Moonwalk: Memory-Efficient Gradient Computation Method
Discover Moonwalk, a novel technique that reduces memory use in deep learning by optimizing gradient computation without storing activations.
Language-Guided Network for Camouflaged Object Detection
Discover the Language-Guided Structure-Aware Network (LGSAN) that improves camouflaged object detection using text and visual features for higher accuracy.
Boost Deepfake Audio Detection with Neuron Dropin & Plasticity
Improve deepfake audio detection accuracy and efficiency using neuron-level dropin and neuroplasticity mechanisms that reduce error rates and computation.