SKKU IRIS Lab
SKKU IRIS Lab
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[J8] CAMEL: An Adaptive Camera with Embedded Machine Learning Based Sensor Parameter Control
[C24] A Camera with Brain–Embedding Machine Learning in 3D Sensors
[C23] Mixture of Pre-processing Experts Model for Noise Robust Deep Learning on Resource Constrained Platforms
[C22] Edge-Host Partitioning of Deep Neural Networks with Feature Space Encoding for Resource-Constrained Internet-of-Things Platforms
[J6] 3-D Stacked Image Sensor With Deep Neural Network Computation
[J5] An Energy-Quality Scalable Wireless Image Sensor Node for Object-Based Video Surveillance
[C19] Cascade Adversarial Machine Learning Regularized with a Unified Embedding
[C16] A Unified Embedding for Image Classification and Pixel-Level Regularization
[J4] Design and Analysis of a Neural Network Inference Engine based on Adaptive Weight Compression
[C13] Cascade Adversarial Machine Learning Regularized with a Unified Embedding
[C12] Energy-Efficient Neural Image Processing for Internet-of-Things Edge Devices
[C11] Design of an Energy-Efficient Accelerator for Training of Convolutional Neural Networks using Frequency-Domain Computation
[J3] A Single-Chip Image Sensor Node With Energy Harvesting From a CMOS Pixel Array
[J2] Clock Data Compensation Aware Digital Circuits Design for Voltage Margin Reduction
[C10] On-Chip Training of Recurrent Neural Networks with Limited Numerical Precision
[C9] Adaptive Weight Compression for Memory-Efficient Neural Networks
[C8] Clock Data Compensation Aware Clock Tree Synthesis in Digital Circuits with Adaptive Clock Generation
[C7] A Low-Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of-Interest Based Rate Controller
[C6] Reconfigurable 96x128 Active Pixel Sensor with 2.1μW/mm2 Power Generation and Regulated Multi- Domain Power Delivery for Self-Powered Imaging
[C5] An Energy-Efficient Wireless Video Sensor Node with a Region-of-Interest Based Multi-Parameter Rate Controller for Moving Object Surveillance
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