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Real-Time Object Detection and Localization in Compressive Sensed Video on Embedded Hardware
Every day around the world, interminable terabytes of data are being cap...
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CUDA: Contradistinguisher for Unsupervised Domain Adaptation
In this paper, we propose a simple model referred as Contradistinguisher...
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EvAn: Neuromorphic Event-based Anomaly Detection
Event-based cameras are bio-inspired novel sensors that asynchronously r...
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GAN-Tree: An Incrementally Learned Hierarchical Generative Framework for Multi-Modal Data Distributions
Despite the remarkable success of generative adversarial networks, their...
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Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images
In the emerging commercial space industry there is a drastic increase in...
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Fast High-Dimensional Bilateral and Nonlocal Means Filtering
Existing fast algorithms for bilateral and nonlocal means filtering most...
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MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction
Developing accurate, transferable and computationally inexpensive machin...
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The role of surrogate models in the development of digital twins of dynamic systems
Digital twin technology has significant promise, relevance and potential...
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Two Tier Prediction of Stroke Using Artificial Neural Networks and Support Vector Machines
Cerebrovascular accident (CVA) or stroke is the rapid loss of brain func...
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Quantization-Aware Phase Retrieval
We address the problem of phase retrieval (PR) from quantized measuremen...
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A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19
The outbreak of the novel coronavirus (COVID-19) is unfolding as a major...
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Binary Document Image Super Resolution for Improved Readability and OCR Performance
There is a need for information retrieval from large collections of low-...
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Learning to Count in the Crowd from Limited Labeled Data
Recent crowd counting approaches have achieved excellent performance. ho...
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TLU-Net: A Deep Learning Approach for Automatic Steel Surface Defect Detection
Visual steel surface defect detection is an essential step in steel shee...
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One-Shot Object Localization Using Learnt Visual Cues via Siamese Networks
A robot that can operate in novel and unstructured environments must be ...
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Ask, Acquire, and Attack: Data-free UAP Generation using Class Impressions
Deep learning models are susceptible to input specific noise, called adv...
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Fast Adaptive Bilateral Filtering
In the classical bilateral filter, a fixed Gaussian range kernel is used...
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UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation
Aiming towards human-level generalization, there is a need to explore ad...
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Teaching Robots Novel Objects by Pointing at Them
Robots that must operate in novel environments and collaborate with huma...
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Mango Tree Net -- A fully convolutional network for semantic segmentation and individual crown detection of mango trees
This work presents a method for semantic segmentation of mango trees in ...
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Contradistinguisher: Applying Vapnik's Philosophy to Unsupervised Domain Adaptation
A complex combination of simultaneous supervised-unsupervised learning i...
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Learning Stable Manoeuvres in Quadruped Robots from Expert Demonstrations
With the research into development of quadruped robots picking up pace, ...
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Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
We introduce a detection framework for dense crowd counting and eliminat...
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A Re-evaluation of Knowledge Graph Completion Methods
Knowledge Graph Completion (KGC) aims at automatically predicting missin...
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A Naturalness Evaluation Database for Video Prediction Models
The study of video prediction models is believed to be a fundamental app...
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A Dual Framework for Low-rank Tensor Completion
We propose a novel formulation of the low-rank tensor completion problem...
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Groupwise Maximin Fair Allocation of Indivisible Goods
We study the problem of allocating indivisible goods among n agents in a...
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A unified decision making framework for supply and demand management in microgrid networks
This paper considers two important problems - on the supply-side and dem...
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Transfer Learning in CNNs Using Filter-Trees
Convolutional Neural Networks (CNNs) are very effective for many pattern...
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Artifact reduction for separable non-local means
It was recently demonstrated [J. Electron. Imaging, 25(2), 2016] that on...
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Generalized Dropout
Deep Neural Networks often require good regularizers to generalize well....
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Conditions for Stability and Convergence of Set-Valued Stochastic Approximations: Applications to Approximate Value and Fixed point Iterations
The main aim of this paper is the development of easily verifiable suffi...
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SketchParse : Towards Rich Descriptions for Poorly Drawn Sketches using Multi-Task Hierarchical Deep Networks
The ability to semantically interpret hand-drawn line sketches, although...
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CNN Fixations: An unraveling approach to visualize the discriminative image regions
Deep convolutional neural networks (CNN) have revolutionized various fie...
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Switching Convolutional Neural Network for Crowd Counting
We propose a novel crowd counting model that maps a given crowd scene to...
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Confidence estimation in Deep Neural networks via density modelling
State-of-the-art Deep Neural Networks can be easily fooled into providin...
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DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data
A class of recent approaches for generating images, called Generative Ad...
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Deep image representations using caption generators
Deep learning exploits large volumes of labeled data to learn powerful m...
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Amortized Inference and Learning in Latent Conditional Random Fields for Weakly-Supervised Semantic Image Segmentation
Conditional random fields (CRFs) are commonly employed as a post-process...
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Analysis of gradient descent methods with non-diminishing, bounded errors
The main aim of this paper is to provide an analysis of gradient descent...
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Training Sparse Neural Networks
Deep neural networks with lots of parameters are typically used for larg...
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Compensating for Large In-Plane Rotations in Natural Images
Rotation invariance has been studied in the computer vision community pr...
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Enabling My Robot To Play Pictionary : Recurrent Neural Networks For Sketch Recognition
Freehand sketching is an inherently sequential process. Yet, most approa...
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SwiDeN : Convolutional Neural Networks For Depiction Invariant Object Recognition
Current state of the art object recognition architectures achieve impres...
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Inducing Interpretability in Knowledge Graph Embeddings
We study the problem of inducing interpretability in KG embeddings. Spec...
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CANDiS: Coupled & Attention-Driven Neural Distant Supervision
Distant Supervision for Relation Extraction uses heuristically aligned t...
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Event Schema Induction using Tensor Factorization with Back-off
The goal of Event Schema Induction(ESI) is to identify schemas of events...
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Relation Schema Induction using Tensor Factorization with Side Information
Given a set of documents from a specific domain (e.g., medical research ...
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ParMooN - a modernized program package based on mapped finite elements
ParMooN is a program package for the numerical solution of elliptic and...
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Big Data and Fog Computing
Fog computing serves as a computing layer that sits between the edge dev...
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