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07/08/2023
End-to-End Supervised Multilabel Contrastive Learning
Multilabel representation learning is recognized as a challenging proble...
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04/11/2023
Computational Pathology: A Survey Review and The Way Forward
Computational Pathology (CoPath) is an interdisciplinary science that au...
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12/31/2022
Pseudo-Inverted Bottleneck Convolution for DARTS Search Space
Differentiable Architecture Search (DARTS) has attracted considerable at...
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03/31/2022
Exploiting Explainable Metrics for Augmented SGD
Explaining the generalization characteristics of deep learning is an eme...
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01/27/2022
HistoKT: Cross Knowledge Transfer in Computational Pathology
The lack of well-annotated datasets in computational pathology (CPath) o...
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11/28/2021
P4AI: Approaching AI Ethics through Principlism
The field of computer vision is rapidly evolving, particularly in the co...
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11/28/2021
NoFADE: Analyzing Diminishing Returns on CO2 Investment
Climate change continues to be a pressing issue that currently affects s...
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11/28/2021
Towards Robust and Automatic Hyper-Parameter Tunning
The task of hyper-parameter optimization (HPO) is burdened with heavy co...
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10/23/2021
In Search of Probeable Generalization Measures
Understanding the generalization behaviour of deep neural networks is a ...
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10/13/2021
CONetV2: Efficient Auto-Channel Size Optimization for CNNs
Neural Architecture Search (NAS) has been pivotal in finding optimal net...
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08/16/2021
Probeable DARTS with Application to Computational Pathology
AI technology has made remarkable achievements in computational patholog...
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08/15/2021
CONet: Channel Optimization for Convolutional Neural Networks
Neural Architecture Search (NAS) has shifted network design from using h...
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04/18/2021
Reconsidering CO2 emissions from Computer Vision
Climate change is a pressing issue that is currently affecting and will ...
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07/11/2020
FocusLiteNN: High Efficiency Focus Quality Assessment for Digital Pathology
Out-of-focus microscopy lens in digital pathology is a critical bottlene...
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06/11/2020
AdaS: Adaptive Scheduling of Stochastic Gradients
The choice of step-size used in Stochastic Gradient Descent (SGD) optimi...
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12/24/2019
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains
Recently proposed methods for weakly-supervised semantic segmentation ha...
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09/18/2019
On the Closed Form Expression of Elementary Symmetric Polynomials and the Inverse of Vandermonde Matrix
Inverse Vandermonde matrix calculation is a long-standing problem to sol...
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11/14/2018
Focus Quality Assessment of High-Throughput Whole Slide Imaging in Digital Pathology
One of the challenges facing the adoption of digital pathology workflows...
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10/25/2018
Convolutional Deblurring for Natural Imaging
In this paper, we propose a novel design of image deblurring in the form...
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09/01/2013
High-Accuracy Total Variation for Compressed Video Sensing
Numerous total variation (TV) regularizers, engaged in image restoration...
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11/29/2009
