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Found 6 papers, 1 papers with code
EBM Life Cycle: MCMC Strategies for Synthesis, Defense, and Density Modeling
This work presents strategies to learn an Energy-Based Model (EBM) according to the desired length of its MCMC sampling trajectories.
Memory-Efficient CNN Accelerator Based on Interlayer Feature Map Compression
To maintain real-time processing in embedded systems, large on-chip memory is required to buffer the interlayer feature maps.
An Analog Neural Network Computing Engine using CMOS-Compatible Charge-Trap-Transistor (CTT)
The proposed computing engine is composed of a scalable CTT multiplier array and energy efficient analog-digital interfaces.
A Streaming Accelerator for Deep Convolutional Neural Networks with Image and Feature Decomposition for Resource-limited System Applications
Deep convolutional neural networks (CNN) are widely used in modern artificial intelligence (AI) and smart vision systems but also limited by computation latency, throughput, and energy efficiency on a resource-limited scenario, such as mobile devices, internet of things (IoT), unmanned aerial vehicles (UAV), and so on.
A Reconfigurable Streaming Deep Convolutional Neural Network Accelerator for Internet of Things
To implement image detection using CNN in the internet of things (IoT) devices, a streaming hardware accelerator is proposed.
