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Found 5 papers, 0 papers with code
Continuous Reinforcement Learning-based Dynamic Difficulty Adjustment in a Visual Working Memory Game
In this paper, we propose a continuous RL-based DDA methodology for a visual working memory (VWM) game to handle the complex search space for the difficulty of memorization.
Models Developed for Spiking Neural Networks
Spiking neural networks (SNNs) have been around for a long time, and they have been investigated to understand the dynamics of the brain.
A Novel Approximate Hamming Weight Computing for Spiking Neural Networks: an FPGA Friendly Architecture
Hamming weights of sparse and long binary vectors are important modules in many scientific applications, particularly in spiking neural networks that are of our interest.
Attention-based Assisted Excitation for Salient Object Detection
In this paper, object-based attention in human visual cortex inspires us to introduce a mechanism for modification of activations in feature maps of CNNs.
Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs
We conducted two sets of experiments based on two different protocols of OSV, i. e., writer-dependent and writer-independent on three signature datasets: GPDS-Synthetic, MCYT, and UT-SIG.
