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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...
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Distillating Knowledge from Graph Convolutional Networks
Existing knowledge distillation methods focus on convolutional neural ne...
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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...
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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...
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AdderNet: Do We Really Need Multiplications in Deep Learning?
Compared with cheap addition operation, multiplication operation is of m...
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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...
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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...
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A Regularization Approach for Instance-Based Superset Label Learning
Different from the traditional supervised learning in which each trainin...
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GhostNet: More Features from Cheap Operations
Deploying convolutional neural networks (CNNs) on embedded devices is di...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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A Review of Computer Vision Methods in Network Security
Network security has become an area of significant importance more than ...
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An Underwater Image Enhancement Benchmark Dataset and Beyond
Underwater image enhancement has been attracting much attention due to i...
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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 ...
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GradNet: Gradient-Guided Network for Visual Object Tracking
The fully-convolutional siamese network based on template matching has s...
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Deep Multimodal Neural Architecture Search
Designing effective neural networks is fundamentally important in deep m...
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Local Deep-Feature Alignment for Unsupervised Dimension Reduction
This paper presents an unsupervised deep-learning framework named Local ...
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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...
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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...
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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...
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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...
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Transfer Metric Learning: Algorithms, Applications and Outlooks
Distance metric learning (DML) aims to find an appropriate way to reveal...
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Distilling portable Generative Adversarial Networks for Image Translation
Despite Generative Adversarial Networks (GANs) have been widely used in ...
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Fast Efficient Object Detection Using Selective Attention
Deep learning object detectors achieve state-of-the-art accuracy at the ...
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EcoNAS: Finding Proxies for Economical Neural Architecture Search
Neural Architecture Search (NAS) achieves significant progress in many c...
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Discernible Compressed Images via Deep Perception Consistency
Image compression, as one of the fundamental low-level image processing ...
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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...
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HourNAS: Extremely Fast Neural Architecture Search Through an Hourglass Lens
Neural Architecture Search (NAS) refers to automatically design the arch...
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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...
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Fully-Featured Attribute Transfer
Image attribute transfer aims to change an input image to a target one w...
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Data-Free Learning of Student Networks
Learning portable neural networks is very essential for computer vision ...
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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 ...
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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...
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RNAS: Architecture Ranking for Powerful Networks
Neural Architecture Search (NAS) is attractive for automatically produci...
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Towards High Performance Human Keypoint Detection
Human keypoint detection from a single image is very challenging due to ...
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Multimodal Unified Attention Networks for Vision-and-Language Interactions
Learning an effective attention mechanism for multimodal data is importa...
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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 ...
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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...
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Learning Student Networks via Feature Embedding
Deep convolutional neural networks have been widely used in numerous app...
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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...
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Segmentation-Aware Image Denoising without Knowing True Segmentation
Several recent works discussed application-driven image restoration neur...
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Image Quality Assessment for Perceptual Image Restoration: A New Dataset, Benchmark and Metric
Image quality assessment (IQA) is the key factor for the fast developmen...
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AM-LFS: AutoML for Loss Function Search
Designing an effective loss function plays an important role in visual a...
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Positive-Unlabeled Compression on the Cloud
Many attempts have been done to extend the great success of convolutiona...
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