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Aug 22, 2019
Computer Vision

Saliency Methods for Explaining Adversarial Attacks

In this work, we aim to explain the classifications of adversary images using saliency methods. Saliency methods explain individual classification de…
Aug 22, 2019
Computer Vision
Robotics

Object detection on aerial imagery using CenterNet

Detection and classification of objects in aerial imagery have several applications like urban planning, crop surveillance, and traffic surveillance.…
Aug 22, 2019
Social and Information Networks
Machine Learning

motif2vec: Motif Aware Node Representation Learning for Heterogeneous…

Recent years have witnessed a surge of interest in machine learning on graphs and networks with applications ranging from vehicular network design to…
Aug 22, 2019
By kiya
Image and Video Processing
Computer Vision

An Image Fusion Scheme for Single-Shot High Dynamic Range Imaging wit…

This paper proposes a novel multi-exposure image fusion (MEF) scheme for single-shot high dynamic range imaging with spatially varying exposures (SVE…
Aug 22, 2019
Computer Vision

Multi-Stream Single Shot Spatial-Temporal Action Detection

We present a 3D Convolutional Neural Networks (CNNs) based single shot detector for spatial-temporal action detection tasks. Our model includes: (1) …
Aug 21, 2019
Computer Vision
Distributed
Parallel
and Cluster Computing

MobiSR: Efficient On-Device Super-Resolution through Heterogeneous …

In recent years, convolutional networks have demonstrated unprecedented performance in the image restoration task of super-resolution (SR). SR entail…
Aug 21, 2019
By mha241
Computer Vision

DomainSiam: Domain-Aware Siamese Network for Visual Object Tracking

Visual object tracking is a fundamental task in the field of computer vision. Recently, Siamese trackers have achieved state-of-the-art performance o…
Aug 21, 2019
Machine Learning
Image and Video Processing

Representation Disentanglement for Multi-task Learning with applicati…

One of the biggest challenges for deep learning algorithms in medical image analysis is the indiscriminate mixing of image properties, e.g. artifacts…
Aug 21, 2019
By tianli
Machine Learning
Distributed
Parallel
and Cluster Computing

Federated Learning: Challenges, Methods, and Future Directions

Federated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping…
Aug 21, 2019
Computation and Language

In this work, we introduced WikiCREM, a large dataset of training instances for pronoun resolution. We use our dataset to fine-tune the Bert language model. Our results match or outperform state-of-the-art models on 6 out of 7 evaluated datasets.

WikiCREM: A Large Unsupervised Corpus for Coreference Resolution

Pronoun resolution is a major area of natural language understanding. However, large-scale training sets are still scarce, since manually labelling d…
Aug 21, 2019
Image and Video Processing
Computer Vision
Machine Learning

A CNN toolbox for skin cancer classification

We describe a software toolbox for the configuration of deep neural networks in the domain of skin cancer classification. The implemented software ar…
Aug 21, 2019
Machine Learning
Computational Finance

This article proposed a one-dimensional convolutional neural network architecture for quantile regression. The model takes as input a series of observations, and directly makes one-step ahead forecasts for arbitrary quantiles. It is essentially a co…

QCNN: Quantile Convolutional Neural Network

A dilated causal one-dimensional convolutional neural network architecture is proposed for quantile regression. The model can forecast any arbitrary …
Aug 21, 2019
Applications
Machine Learning

Importance of spatial predictor variable selection in machine learnin…

Machine learning algorithms find frequent application in spatial prediction of biotic and abiotic environmental variables. However, the characteristi…
Aug 21, 2019
Image and Video Processing
Computer Vision
Machine Learning

U-Net Training with Instance-Layer Normalization

Normalization layers are essential in a Deep Convolutional Neural Network (DCNN). Various normalization methods have been proposed. The statistics us…
Aug 21, 2019
By fhaoshu
Computer Vision

InstaBoost: Boosting Instance Segmentation via Probability Map Guided…

Instance segmentation requires a large number of training samples to achieve satisfactory performance and benefits from proper data augmentation. To …
Aug 21, 2019
Artificial Intelligence

Technical Report on Implementing Ranking-Based Semantics in ConArg

ConArg is a suite of tools that offers a wide series of applications for dealing with argumentation problems. In this work, we present the advances w…
Aug 21, 2019
Computation and Language

Predict Emoji Combination with Retrieval Strategy

As emojis are widely used in social media, people not only use an emoji to express their emotions or mention things but also extend its usage to repr…
Aug 21, 2019
Computer Vision
Sound
Audio and Speech Processing
Image and Video Processing

A Realistic Face-to-Face Conversation System based on Deep Neural N…

To improve the experiences of face-to-face conversation with avatar, this paper presents a novel conversation system. It is composed of two sequence-…
Aug 21, 2019
Computer Vision

RBCN: Rectified Binary Convolutional Networks for Enhancing the Per…

Binarized convolutional neural networks (BCNNs) are widely used to improve memory and computation efficiency of deep convolutional neural networks (D…
Aug 21, 2019
Image and Video Processing
Computer Vision

Automated Multi-sequence Cardiac MRI Segmentation Using Supervised …

Left ventricle segmentation and morphological assessment are essential for improving diagnosis and our understanding of cardiomyopathy, which in turn…
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