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07/27/2023
Multiscale Dynamic Graph Representation for Biometric Recognition with Occlusions
Occlusion is a common problem with biometric recognition in the wild. Th...
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07/08/2023
Autonomy 2.0: The Quest for Economies of Scale
With the advancement of robotics and AI technologies in the past decade,...
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04/15/2023
OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization
Transformer-based large language models (LLMs) have achieved great succe...
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04/06/2023
ImaGen: A General Framework for Generating Memory- and Power-Efficient Image Processing Accelerators
Image processing algorithms are prime targets for hardware acceleration ...
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02/10/2023
FastPoints: A State-of-the-Art Point Cloud Renderer for Unity
In this paper, we introduce FastPoints, a state-of-the-art point cloud r...
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12/05/2022
Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators
As Deep Neural Networks (DNNs) are increasingly deployed in safety criti...
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09/15/2022
Color-Perception-Guided Display Power Reduction for Virtual Reality
Battery life is an increasingly urgent challenge for today's untethered ...
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09/06/2022
Factor Graph Accelerator for LiDAR-Inertial Odometry
Factor graph is a graph representing the factorization of a probability ...
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08/30/2022
ANT: Exploiting Adaptive Numerical Data Type for Low-bit Deep Neural Network Quantization
Quantization is a technique to reduce the computation and memory cost of...
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07/13/2022
Perturbation Inactivation Based Adversarial Defense for Face Recognition
Deep learning-based face recognition models are vulnerable to adversaria...
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02/14/2022
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Quantization of deep neural networks (DNN) has been proven effective for...
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01/04/2022
RTNN: Accelerating Neighbor Search Using Hardware Ray Tracing
Neighbor search is of fundamental important to many engineering and scie...
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12/16/2021
Block-Skim: Efficient Question Answering for Transformer
Transformer models have achieved promising results on natural language p...
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10/08/2021
Characterizing and Demystifying the Implicit Convolution Algorithm on Commercial Matrix-Multiplication Accelerators
Many of today's deep neural network accelerators, e.g., Google's TPU and...
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09/15/2021
The Promise of Dataflow Architectures in the Design of Processing Systems for Autonomous Machines
The commercialization of autonomous machines is a thriving sector, and l...
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07/19/2021
ZIPPER: Exploiting Tile- and Operator-level Parallelism for General and Scalable Graph Neural Network Acceleration
Graph neural networks (GNNs) start to gain momentum after showing signif...
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07/16/2021
S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration
Exploiting sparsity is a key technique in accelerating quantized convolu...
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06/17/2021
Resurrect3D: An Open and Customizable Platform for Visualizing and Analyzing Cultural Heritage Artifacts
Art and culture, at their best, lie in the act of discovery and explorat...
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05/11/2021
One Shot Face Swapping on Megapixels
Face swapping has both positive applications such as entertainment, huma...
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03/30/2021
The Matter of Time – A General and Efficient System for Precise Sensor Synchronization in Robotic Computing
Time synchronization is a critical task in robotic computing such as aut...
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12/19/2020
Digital Reconstruction of Elmina Castle for Mobile Virtual Reality via Point-based Detail Transfer
Reconstructing 3D models from large, dense point clouds is critical to e...
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11/23/2020
End-to-End Framework for Efficient Deep Learning Using Metasurfaces Optics
Deep learning using Convolutional Neural Networks (CNNs) has been shown ...
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09/13/2020
A Survey of FPGA-Based Robotic Computing
Recent researches on robotics have shown significant improvement, spanni...
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08/29/2020
Accelerating Sparse DNN Models without Hardware-Support via Tile-Wise Sparsity
Network pruning can reduce the high computation cost of deep neural netw...
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08/23/2020
Ptolemy: Architecture Support for Robust Deep Learning
Deep learning is vulnerable to adversarial attacks, where carefully-craf...
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02/18/2020
Balancing Efficiency and Flexibility for DNN Acceleration via Temporal GPU-Systolic Array Integration
The research interest in specialized hardware accelerators for deep neur...
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11/16/2019
Tigris: Architecture and Algorithms for 3D Perception in Point Clouds
Machine perception applications are increasingly moving toward manipulat...
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10/14/2019
Learning Sparsity and Quantization Jointly and Automatically for Neural Network Compression via Constrained Optimization
Deep Neural Networks (DNNs) are widely applied in a wide range of usecas...
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04/17/2019
Adversarial Defense Through Network Profiling Based Path Extraction
Recently, researchers have started decomposing deep neural network model...
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01/31/2019
Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework
Iris segmentation and localization in non-cooperative environment is cha...
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12/05/2018
ECC: Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model
Many DNN-enabled vision applications constantly operate under severe ene...
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10/17/2018
Recognizing Partial Biometric Patterns
Biometric recognition on partial captured targets is challenging, where ...
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10/16/2018
SCALE-Sim: Systolic CNN Accelerator Simulator
Systolic Arrays are one of the most popular compute substrates within De...
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10/16/2018
SCALE-Sim: Systolic CNN Accelerator
Systolic Arrays are one of the most popular compute substrates within De...
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06/12/2018
End-to-End Learning of Energy-Constrained Deep Neural Networks
Deep Neural Networks (DNN) are increasingly deployed in highly energy-co...
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03/29/2018
Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision
Continuous computer vision (CV) tasks increasingly rely on convolutional...
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02/15/2018
Cloud No Longer a Silver Bullet, Edge to the Rescue
This paper takes the position that, while cognitive computing today reli...
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01/19/2018