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Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks

Deep neural networks often consist of a great number of trainable parame...
02/23/2020 ∙ by Yehui Tang, et al. ∙ 72 ∙ share

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Distillating Knowledge from Graph Convolutional Networks

Existing knowledge distillation methods focus on convolutional neural ne...
03/23/2020 ∙ by Yiding Yang, et al. ∙ 70 ∙ share

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Learning Frequency-aware Dynamic Network for Efficient Super-Resolution

Deep learning based methods, especially convolutional neural networks (C...
03/15/2021 ∙ by Wenbin Xie, et al. ∙ 48 ∙ share

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Deep Conversational Recommender Systems: A New Frontier for Goal-Oriented Dialogue Systems

In recent years, the emerging topics of recommender systems that take ad...
04/28/2020 ∙ by Dai Hoang Tran, et al. ∙ 37 ∙ share

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AdderNet and its Minimalist Hardware Design for Energy-Efficient Artificial Intelligence

Convolutional neural networks (CNN) have been widely used for boosting t...
01/25/2021 ∙ by Yunhe Wang, et al. ∙ 35 ∙ share

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AdderNet: Do We Really Need Multiplications in Deep Learning?

Compared with cheap addition operation, multiplication operation is of m...
12/31/2019 ∙ by Hanting Chen, et al. ∙ 31 ∙ share

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Robust Visual Tracking Revisited: From Correlation Filter to Template Matching

In this paper, we propose a novel matching based tracker by investigatin...
04/15/2019 ∙ by Fanghui Liu, et al. ∙ 26 ∙ share

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A Unified End-to-End Framework for Efficient Deep Image Compression

Image compression is a widely used technique to reduce the spatial redun...
02/09/2020 ∙ by Jiaheng Liu, et al. ∙ 25 ∙ share

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A Regularization Approach for Instance-Based Superset Label Learning

Different from the traditional supervised learning in which each trainin...
04/05/2019 ∙ by Chen gong, et al. ∙ 24 ∙ share

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GhostNet: More Features from Cheap Operations

Deploying convolutional neural networks (CNNs) on embedded devices is di...
11/27/2019 ∙ by Kai Han, et al. ∙ 23 ∙ share

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A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection

Deep learning-based computer vision is usually data-hungry. Many researc...
12/15/2019 ∙ by Zhe Chen, et al. ∙ 23 ∙ share

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Self-Supervised Learning Framework for Remote Heart Rate Estimation Using Spatiotemporal Augmentation

Recent supervised deep learning methods have shown that heart rate can b...
07/16/2021 ∙ by Hao Wang, et al. ∙ 23 ∙ share

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Stacked Semantic-Guided Network for Zero-Shot Sketch-Based Image Retrieval

Zero-shot sketch-based image retrieval (ZS-SBIR) is a task of cross-doma...
04/03/2019 ∙ by Hao Wang, et al. ∙ 22 ∙ share

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All you need is a good representation: A multi-level and classifier-centric representation for few-shot learning

The main problems of few-shot learning are how to learn a generalized re...
11/28/2019 ∙ by Shaoli Huang, et al. ∙ 22 ∙ share

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Gated-GAN: Adversarial Gated Networks for Multi-Collection Style Transfer

Style transfer describes the rendering of an image semantic content as d...
04/04/2019 ∙ by Xinyuan Chen, et al. ∙ 20 ∙ share

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Shakeout: A New Approach to Regularized Deep Neural Network Training

Recent years have witnessed the success of deep neural networks in deali...
04/13/2019 ∙ by Guoliang Kang, et al. ∙ 20 ∙ share

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Progressive Retinex: Mutually Reinforced Illumination-Noise Perception Network for Low Light Image Enhancement

Contrast enhancement and noise removal are coupled problems for low-ligh...
11/26/2019 ∙ by Yang Wang, et al. ∙ 20 ∙ share

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Multi-Agent Meta-Reinforcement Learning for Self-Powered and Sustainable Edge Computing Systems

The stringent requirements of mobile edge computing (MEC) applications a...
02/20/2020 ∙ by Md. Shirajum Munir, et al. ∙ 20 ∙ share

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Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting

Unsupervised domain adaptation (UDA) for nuclei instance segmentation is...
05/05/2020 ∙ by Dongnan Liu, et al. ∙ 19 ∙ share

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A Review of Computer Vision Methods in Network Security

Network security has become an area of significant importance more than ...
05/07/2020 ∙ by Jiawei Zhao, et al. ∙ 19 ∙ share

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An Underwater Image Enhancement Benchmark Dataset and Beyond

Underwater image enhancement has been attracting much attention due to i...
01/11/2019 ∙ by Chongyi Li, et al. ∙ 18 ∙ share

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Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus

The transparent cornea is the window of the eye, facilitating the entry ...
01/31/2020 ∙ by Nicole Hallett, et al. ∙ 18 ∙ share

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GradNet: Gradient-Guided Network for Visual Object Tracking

The fully-convolutional siamese network based on template matching has s...
09/15/2019 ∙ by Peixia Li, et al. ∙ 17 ∙ share

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Deep Multimodal Neural Architecture Search

Designing effective neural networks is fundamentally important in deep m...
04/25/2020 ∙ by Zhou Yu, et al. ∙ 17 ∙ share

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Local Deep-Feature Alignment for Unsupervised Dimension Reduction

This paper presents an unsupervised deep-learning framework named Local ...
04/22/2019 ∙ by Jian Zhang, et al. ∙ 16 ∙ share

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Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks

In the future 6th generation networks, ultra-reliable and low-latency co...
02/22/2020 ∙ by Changyang She, et al. ∙ 16 ∙ share

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Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19

This paper uses new and recently introduced methodologies to study the s...
01/03/2021 ∙ by Nick James, et al. ∙ 15 ∙ share

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Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain

The goal of transfer learning is to improve the performance of target le...
04/08/2019 ∙ by Yong Luo, et al. ∙ 14 ∙ share

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Semi-supervised Learning Approach to Generate Neuroimaging Modalities with Adversarial Training

Magnetic Resonance Imaging (MRI) of the brain can come in the form of di...
12/09/2019 ∙ by Harrison Nguyen, et al. ∙ 14 ∙ share

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Transfer Metric Learning: Algorithms, Applications and Outlooks

Distance metric learning (DML) aims to find an appropriate way to reveal...
10/09/2018 ∙ by Yong Luo, et al. ∙ 13 ∙ share

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Distilling portable Generative Adversarial Networks for Image Translation

Despite Generative Adversarial Networks (GANs) have been widely used in ...
03/07/2020 ∙ by Hanting Chen, et al. ∙ 13 ∙ share

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Fast Efficient Object Detection Using Selective Attention

Deep learning object detectors achieve state-of-the-art accuracy at the ...
11/19/2018 ∙ by Shivanthan Yohanandan, et al. ∙ 12 ∙ share

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EcoNAS: Finding Proxies for Economical Neural Architecture Search

Neural Architecture Search (NAS) achieves significant progress in many c...
01/05/2020 ∙ by Dongzhan Zhou, et al. ∙ 12 ∙ share

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Discernible Compressed Images via Deep Perception Consistency

Image compression, as one of the fundamental low-level image processing ...
02/17/2020 ∙ by Zhaohui Yang, et al. ∙ 12 ∙ share

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Conservative Plane Releasing for Spatial Privacy Protection in Mixed Reality

Augmented reality (AR) or mixed reality (MR) platforms require spatial u...
04/17/2020 ∙ by Jaybie A. de Guzman, et al. ∙ 12 ∙ share

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HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens

Neural Architecture Search (NAS) refers to automatically design the arch...
05/29/2020 ∙ by Zhaohui Yang, et al. ∙ 12 ∙ share

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Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving

The strong demand of autonomous driving in the industry has lead to stro...
11/27/2020 ∙ by Zhenxun Yuan, et al. ∙ 12 ∙ share

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Fully-Featured Attribute Transfer

Image attribute transfer aims to change an input image to a target one w...
02/17/2019 ∙ by De Xie, et al. ∙ 10 ∙ share

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Data-Free Learning of Student Networks

Learning portable neural networks is very essential for computer vision ...
04/02/2019 ∙ by Hanting Chen, et al. ∙ 10 ∙ share

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Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification

Deep learning has recently attracted significant attention in the field ...
04/04/2019 ∙ by Cheng Deng, et al. ∙ 10 ∙ share

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Robust and Discriminative Labeling for Multi-label Active Learning Based on Maximum Correntropy Criterion

Multi-label learning draws great interests in many real world applicatio...
04/14/2019 ∙ by Bo Du, et al. ∙ 10 ∙ share

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RNAS: Architecture Ranking for Powerful Networks

Neural Architecture Search (NAS) is attractive for automatically produci...
09/30/2019 ∙ by Yixing Xu, et al. ∙ 10 ∙ share

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Towards High Performance Human Keypoint Detection

Human keypoint detection from a single image is very challenging due to ...
02/03/2020 ∙ by Jing Zhang, et al. ∙ 10 ∙ share

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Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detection

As a crucial task of autonomous driving, 3D object detection has made gr...
07/29/2021 ∙ by Yinmin Zhang, et al. ∙ 10 ∙ share

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Multimodal Unified Attention Networks for Vision-and-Language Interactions

Learning an effective attention mechanism for multimodal data is importa...
08/12/2019 ∙ by Zhou Yu, et al. ∙ 9 ∙ share

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Epileptic Seizure Classification with Symmetric and Hybrid Bilinear Models

Epilepsy affects nearly 1 be treated by anti-epileptic drugs and a much ...
01/15/2020 ∙ by Tennison Liu, et al. ∙ 9 ∙ share

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One-Shot Affordance Detection

Affordance detection refers to identifying the potential action possibil...
06/28/2021 ∙ by Hongchen Luo, et al. ∙ 9 ∙ share

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Computer vision-based framework for extracting geological lineaments from optical remote sensing data

The extraction of geological lineaments from digital satellite data is a...
10/04/2018 ∙ by Ehsan Farahbakhsh, et al. ∙ 8 ∙ share

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Learning Student Networks via Feature Embedding

Deep convolutional neural networks have been widely used in numerous app...
12/17/2018 ∙ by Hanting Chen, et al. ∙ 8 ∙ share

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Adapting Stochastic Block Models to Power-Law Degree Distributions

Stochastic block models (SBMs) have been playing an important role in mo...
04/05/2019 ∙ by Maoying Qiao, et al. ∙ 8 ∙ share

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