NEXUS: A 28nm 3.3 pJ/SOP 16-Core Spiking Neural Network with a Diamond Topology for Real-Time Data Processing
The realization of brain-scale spiking neural networks (SNNs) is impeded by power
constraints and low integration density. To address these challenges, multi-core SNNs are …
constraints and low integration density. To address these challenges, multi-core SNNs are …
A 3-D Multi-Precision Scalable Systolic FMA Architecture
Artificial Intelligence (AI) has almost become the default approach in a wide range of
applications, such as computer vision, chatbots, and natural language processing. These AI …
applications, such as computer vision, chatbots, and natural language processing. These AI …
The Impact of Implementing Hybrid Learning on Flexibility and Quality of Learning
S Rijal, Z Wei, D Jiao, Y Wang - … Emerging Technologies in …, 2024 - journal.ypidathu.or.id
Background: The implementation of hybrid learning is a learning method that refers to a
learning method that combines or combines face-to-face and online-based learning. By …
learning method that combines or combines face-to-face and online-based learning. By …
[PDF][PDF] Artificial Intelligence of Things (AIoT): Integration Challenges and Security Issues
Abstract AIoT stands for Artificial Intelligence of Things and refers to the synergy between
Internet of Things and artificial intelligence, where new frontiers are opening for developing …
Internet of Things and artificial intelligence, where new frontiers are opening for developing …
SDM-SNN: Sparse Distributed Memory Using Constant-Weight Fibonacci Code for Spiking Neural Network
YX Zhou, CW Liu - 2024 International VLSI Symposium on …, 2024 - ieeexplore.ieee.org
The long-term memory (LTM) is generally considered as the unlimited and permanent
storage of information in the human brain. This concept has spurred numerous researches …
storage of information in the human brain. This concept has spurred numerous researches …