Intra Mode Derivation
Intra-mode derivation focuses on efficiently determining the optimal representation (mode) for data, bypassing traditional computationally expensive methods. Current research explores this across diverse fields, employing techniques like Hopfield-like matrix decompositions for spiking neural networks and contrastive learning with M-mode image generation for echocardiogram analysis, as well as deep learning architectures for video coding. These advancements aim to reduce computational costs and improve accuracy in various applications, ranging from brain-inspired computing to medical image analysis and video compression.
Papers
October 23, 2023
September 7, 2023