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FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.10726-10734

2019

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A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

IEEE transaction on neural networks and learning systems, 2022-02, Vol.33 (2), p.473-493

2022

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SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation

Computer Vision - ECCV 2020, 2020, Vol.12373, p.1-19

2020

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Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, p.9127-9135

2018

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ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, p.11390-11399

2019

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Influence factors for upper respiratory tract infection in Chinese rural children: A cross-sectional study

Frontiers in pediatrics, 2022-12, Vol.10, p.954363-954363

2022

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Efficient per-element distortion contribution analysis via Harmonic Balance adjoints

Proceedings of the IEEE 2014 Custom Integrated Circuits Conference, 2014, p.1-4

2014

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MAPP: The Berkeley Model and Algorithm Prototyping Platform

2015 IEEE Custom Integrated Circuits Conference (CICC), 2015, p.1-8

2015

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FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, p.12962-12971

2020

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Poster: MAPP: The Berkeley Model and Algorithm Prototyping Platform

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, 2015, Vol.2, p.825-826

2015

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SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, p.1887-1893

2018

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SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

2019 International Conference on Robotics and Automation (ICRA), 2019, p.4376-4382

2019

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Cross-Domain Adaptive Teacher for Object Detection

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, p.7571-7580

2022

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Sustained release of tulobuterol from graphene oxide laden hydrogel to manage asthma

Journal of biomaterials science. Polymer ed., 2021-03, Vol.32 (4), p.524-535

2021

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FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, p.16271-16280

2021

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Time-domain segmentation based massively parallel simulation for ADCs

2013 50th ACM/EDAC/IEEE Design Automation Conference (DAC), 2013, p.1-6

2013

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LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking

2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019, p.265-272

2019

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p14ARF ameliorates inflammation and airway remodeling in nitric acid aerosol inhalation-induced bronchiolitis obliterans

Experimental lung research, 2023-12, Vol.49 (1), p.27-38

2023

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Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.7061-7070

2023

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An Investigation on Hardware-Aware Vision Transformer Scaling

ACM transactions on embedded computing systems, 2024-05, Vol.23 (3), p.1-19, Article 52

2024

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FP-NAS: Fast Probabilistic Neural Architecture Search

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, p.15134-15143

2021

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SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017, p.446-454

2017

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Efficient Deep Neural Networks

Wu, Bichen

2019

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You Only Group Once: Efficient Point-Cloud Processing with Token Representation and Relation Inference Module

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, p.4589-4596

2021

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Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.14431-14442

2023

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FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation

Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions

ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation

Influence factors for upper respiratory tract infection in Chinese rural children: A cross-sectional study

Efficient per-element distortion contribution analysis via Harmonic Balance adjoints

MAPP: The Berkeley Model and Algorithm Prototyping Platform

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

Poster: MAPP: The Berkeley Model and Algorithm Prototyping Platform

SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud

Cross-Domain Adaptive Teacher for Object Detection

Sustained release of tulobuterol from graphene oxide laden hydrogel to manage asthma

FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining

Time-domain segmentation based massively parallel simulation for ADCs

LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking

p14ARF ameliorates inflammation and airway remodeling in nitric acid aerosol inhalation-induced bronchiolitis obliterans

Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP

An Investigation on Hardware-Aware Vision Transformer Scaling

FP-NAS: Fast Probabilistic Neural Architecture Search

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Efficient Deep Neural Networks

You Only Group Once: Efficient Point-Cloud Processing with Token Representation and Relation Inference Module

Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference

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