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Found 7 papers, 1 papers with code
Scaling Up Computer Vision Neural Networks Using Fast Fourier Transform
Deep Learning-based Computer Vision field has recently been trying to explore larger kernels for convolution to effectively scale up Convolutional Neural Networks.
Indian Commercial Truck License Plate Detection and Recognition for Weighbridge Automation
Detection and recognition of a licence plate is important when automating weighbridge services.
Emergent Discrete Communication in Semantic Spaces
Neural agents trained in reinforcement learning settings can learn to communicate among themselves via discrete tokens, accomplishing as a team what agents would be unable to do alone.
Adaptive Agent Architecture for Real-time Human-Agent Teaming
Previous human-human team research have shown complementary policies in TSF game and diversity in human players' skill, which encourages us to relax the assumptions on human policy.
Addressing reward bias in Adversarial Imitation Learning with neutral reward functions
Generative Adversarial Imitation Learning suffers from the fundamental problem of reward bias stemming from the choice of reward functions used in the algorithm.
Deep Variational Inference Without Pixel-Wise Reconstruction
Variational autoencoders (VAEs), that are built upon deep neural networks have emerged as popular generative models in computer vision.
