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Low-Power Hardware-Based Deep-Learning Diagnostics Support Case Study
Deep learning research has generated widespread interest leading to emergence of a large variety of technological innovations and applications.
Memory-Oriented Design-Space Exploration of Edge-AI Hardware for XR Applications
Low-Power Edge-AI capabilities are essential for on-device extended reality (XR) applications to support the vision of Metaverse.
Exploration of Optimized Semantic Segmentation Architectures for edge-Deployment on Drones
In this paper, we present an analysis on the impact of network parameters for semantic segmentation architectures in context of UAV data processing.
Methodology for Realizing VMM with Binary RRAM Arrays: Experimental Demonstration of Binarized-ADALINE Using OxRAM Crossbar
Post weight generation the OxRAM array is carefully programmed to binary weight-states using the proposed weight mapping technique on a custom-built testbench.
Design Exploration of Hybrid CMOS-OxRAM Deep Generative Architectures
To validate the proposed scheme we have simulated two different architectures: (i) Deep Belief Network (DBN) and (ii) Stacked Denoising Autoencoder for classification and reconstruction of hand-written digits from a reduced MNIST dataset of 6000 images.
