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07/04/2023
ProtoDiffusion: Classifier-Free Diffusion Guidance with Prototype Learning
Diffusion models are generative models that have shown significant advan...
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04/02/2023
Textile Pattern Generation Using Diffusion Models
The problem of text-guided image generation is a complex task in Compute...
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03/07/2023
GaussianMLR: Learning Implicit Class Significance via Calibrated Multi-Label Ranking
Existing multi-label frameworks only exploit the information deduced fro...
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02/21/2023
Climate Model Driven Seasonal Forecasting Approach with Deep Learning
Understanding seasonal climatic conditions is critical for better manage...
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12/08/2022
RLSEP: Learning Label Ranks for Multi-label Classification
Multi-label ranking maps instances to a ranked set of predicted labels f...
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10/23/2022
Symmetry and Variance: Generative Parametric Modelling of Historical Brick Wall Patterns
This study integrates artificial intelligence and computational design t...
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06/28/2022
GAN-based Intrinsic Exploration For Sample Efficient Reinforcement Learning
In this study, we address the problem of efficient exploration in reinfo...
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06/22/2022
How to Combine Variational Bayesian Networks in Federated Learning
Federated Learning enables multiple data centers to train a central mode...
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03/02/2022
Continual Learning of Multi-modal Dynamics with External Memory
We study the problem of fitting a model to a dynamical environment when ...
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08/09/2021
Detecting Visual Design Principles in Art and Architecture through Deep Convolutional Neural Networks
Visual design is associated with the use of some basic design elements a...
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08/06/2021
Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation
In recent years, deep learning based methods have shown success in essen...
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06/02/2021
Evidential Turing Processes
A probabilistic classifier with reliable predictive uncertainties i) fit...
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04/13/2021
Single Image Depth Estimation: An Overview
We review solutions to the problem of depth estimation, arguably the mos...
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12/08/2020
ODFNet: Using orientation distribution functions to characterize 3D point clouds
Learning new representations of 3D point clouds is an active research ar...
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11/03/2020
Exploring DeshuffleGANs in Self-Supervised Generative Adversarial Networks
Generative Adversarial Networks (GANs) have become the most used network...
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10/14/2020
A New Distributional Ranking Loss With Uncertainty: Illustrated in Relative Depth Estimation
We propose a new approach for the problem of relative depth estimation f...
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10/14/2020
Relative Depth Estimation as a Ranking Problem
We present a formulation of the relative depth estimation from a single ...
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09/14/2020
EfficientSeg: An Efficient Semantic Segmentation Network
Deep neural network training without pre-trained weights and few data is...
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06/30/2020
Rethinking CNN-Based Pansharpening: Guided Colorization of Panchromatic Images via GANs
Convolutional Neural Networks (CNN)-based approaches have shown promisin...
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06/15/2020
DeshuffleGAN: A Self-Supervised GAN to Improve Structure Learning
Generative Adversarial Networks (GANs) triggered an increased interest i...
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01/17/2020
CHAOS Challenge – Combined (CT-MR) Healthy Abdominal Organ Segmentation
Segmentation of abdominal organs has been a comprehensive, yet unresolve...
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09/17/2018
Multi Modal Convolutional Neural Networks for Brain Tumor Segmentation
In this work, we propose a multi-modal Convolutional Neural Network (CNN...
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09/17/2018
Multi Modal Convolutional Neural Networks forBrain Tumor Segmentation
In this work, we propose a multi-modal Convolutional Neural Network (CNN...
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04/12/2018
Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI
Magnetic Resonance Angiography (MRA) has become an essential MR contrast...
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03/20/2018
Patch-Based Image Inpainting with Generative Adversarial Networks
Area of image inpainting over relatively large missing regions recently ...
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12/31/2017