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06/06/2023
GMMap: Memory-Efficient Continuous Occupancy Map Using Gaussian Mixture Model
Energy consumption of memory accesses dominates the compute energy in en...
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05/22/2023
HighLight: Efficient and Flexible DNN Acceleration with Hierarchical Structured Sparsity
Due to complex interactions among various deep neural network (DNN) opti...
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04/17/2023
RAELLA: Reforming the Arithmetic for Efficient, Low-Resolution, and Low-Loss Analog PIM: No Retraining Required!
Processing-In-Memory (PIM) accelerators have the potential to efficientl...
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10/07/2022
Efficient Computation of Map-scale Continuous Mutual Information on Chip in Real Time
Exploration tasks are essential to many emerging robotics applications, ...
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09/21/2022
Gemino: Practical and Robust Neural Compression for Video Conferencing
Video conferencing systems suffer from poor user experience when network...
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07/14/2022
Developing a Series of AI Challenges for the United States Department of the Air Force
Through a series of federal initiatives and orders, the U.S. Government ...
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05/12/2022
Sparseloop: An Analytical Approach To Sparse Tensor Accelerator Modeling
In recent years, many accelerators have been proposed to efficiently pro...
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09/01/2021
Searching for Efficient Multi-Stage Vision Transformers
Vision Transformer (ViT) demonstrates that Transformer for natural langu...
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03/31/2021
NetAdaptV2: Efficient Neural Architecture Search with Fast Super-Network Training and Architecture Optimization
Neural architecture search (NAS) typically consists of three main steps:...
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02/02/2020
Depth Map Estimation of Dynamic Scenes Using Prior Depth Information
Depth information is useful for many applications. Active depth sensors ...
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12/18/2019
Design Considerations for Efficient Deep Neural Networks on Processing-in-Memory Accelerators
This paper describes various design considerations for deep neural netwo...
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05/06/2019
FSMI: Fast computation of Shannon Mutual Information for information-theoretic mapping
Exploration tasks are embedded in many robotics applications, such as se...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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03/08/2019
FastDepth: Fast Monocular Depth Estimation on Embedded Systems
Depth sensing is a critical function for robotic tasks such as localizat...
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02/13/2019
DeeperLab: Single-Shot Image Parser
We present a single-shot, bottom-up approach for whole image parsing. Wh...
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09/15/2018
Navion: A 2mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones
This paper presents Navion, an energy-efficient accelerator for visual-i...
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07/10/2018
Eyeriss v2: A Flexible and High-Performance Accelerator for Emerging Deep Neural Networks
The design of DNNs has increasingly focused on reducing the computationa...
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04/09/2018
NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications
This work proposes an automated algorithm, called NetAdapt, that adapts ...
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03/27/2017
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
Deep neural networks (DNNs) are currently widely used for many artificia...
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03/17/2017
Towards Closing the Energy Gap Between HOG and CNN Features for Embedded Vision
Computer vision enables a wide range of applications in robotics/drones,...
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12/22/2016
Hardware for Machine Learning: Challenges and Opportunities
Machine learning plays a critical role in extracting meaningful informat...
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11/16/2016
Designing Energy-Efficient Convolutional Neural Networks using Energy-Aware Pruning
Deep convolutional neural networks (CNNs) are indispensable to state-of-...
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07/27/2016
A 58.6mW Real-Time Programmable Object Detector with Multi-Scale Multi-Object Support Using Deformable Parts Model on 1920x1080 Video at 30fps
This paper presents a programmable, energy-efficient and real-time objec...
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03/29/2016
