Abstract Deep Convolutional Neural Network (CNN) is a special type of Neural Networks,
which has shown exemplary performance on several competitions related to Computer …

The recently proposed Conformer model has become the de facto backbone model for
various downstream speech tasks based on its hybrid attention-convolution architecture that …

Cardiovascular diseases affect approximately 50 million people worldwide; thus, heart
disease prevention is one of the most important tasks of any health care system. Despite the …

The rapid development and application of foundation models have revolutionized the field of
artificial intelligence. Large diffusion models have gained significant attention for their ability …

In this work a novel architecture, named pseudo-softmax, to compute an approximated form
of the softmax function is presented. This architecture can be fruitfully used in the last layer of …

Deep neural networks (DNNs) have been widely used in classification due to their high
accuracy. The softmax function is one of the important non-linear functions in DNNs …

In this paper a simplified hardware implementation of a CNN softmax-like layer is proposed.
Initially the softmax activation function is analyzed in terms of required numerical accuracy …

Approximate computing has emerged as a new paradigm that provides power-efficient and
high-performance arithmetic designs by relaxing the stringent requirement of accuracy …

Neural networks can be successfully used to improve several modules of advanced video
coding schemes. In particular, compression of colour components was shown to greatly …

There has been a rapid advance of custom hardware (HW) for accelerating the inference
speed of deep neural networks (DNNs). Previously, the softmax layer was not a main …