Recently, in a lecture room at the Daegu Startup Hub in Dong-gu, Daegu, Kim Soo-pil, a senior researcher at the Daegu ...

Abstract: Recently, sparse coding-based image fusion methods have been developed extensively. Although most of them can produce competitive fusion results, three issues need to be addressed: 1) these ...

Update: See bonito branch for improved performance and experiments using bonito basecalling and other improvements. First, generate a list of read ids to decode using the script util/generate_read_ids ...

This library brings Spatially-sparse convolutional networks to PyTorch. Moreover, it introduces Submanifold Sparse Convolutions, that can be used to build computationally efficient sparse ...

Abstract: The convolutional coding technique is used to encode and decode a continuous stream of bits. The basic concept behind the convolution is the overlapping of two signals to form the other one.

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...

Learning to read results in the formation of a specialized region in the human ventral visual cortex. This region, the visual word form area (VWFA), responds selectively to written words more than to ...

Recently, deep convolutional neural networks (DCNNs) have attained human-level performances on challenging object recognition tasks owing to their complex internal representation. However, it remains ...

Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient.