In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...

Abstract: Graph Convolution Networks (GCNs) have achieved remarkable success in representation of structured graph data. As we know that traditional GCNs are generally defined on the fixed first-order ...

Many people have a desire for self-improvement in one or more life areas, but feel overwhelmed about how to find the time and energy for it. Here's a possible solution for how to work on yourself when ...

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...

Abstract: The morphological undecimated wavelet (MUW) is an efficient feature extraction algorithm for bearing fault diagnosis. Currently, the researched MUW is mainly focused on background noise ...

Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a ...