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09/14/2023
Padding Aware Neurons
Convolutional layers are a fundamental component of most image-related m...
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08/01/2023
Exploring the Role of Explainability in AI-Assisted Embryo Selection
In Vitro Fertilization is among the most widespread treatments for infer...
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11/08/2022
When How to Transfer with Transfer Learning
In deep learning, transfer learning (TL) has become the de facto approac...
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03/21/2022
Healthy Twitter discussions? Time will tell
Studying misinformation and how to deal with unhealthy behaviours within...
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09/28/2021
Who Explains the Explanation? Quantitatively Assessing Feature Attribution Methods
AI explainability seeks to increase the transparency of models, making t...
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09/29/2020
Signs for Ethical AI: A Route Towards Transparency
Artificial Intelligence (AI) has recently raised to the point where it h...
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07/27/2020
A Closer Look at Art Mediums: The MAMe Image Classification Dataset
Art is an expression of human creativity, skill and technology. An excep...
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06/25/2020
Recommendations for machine learning validation in biology
Modern biology frequently relies on machine learning to provide predicti...
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06/10/2020
Global Data Science Project for COVID-19 Summary Report
This paper aims at providing the summary of the Global Data Science Proj...
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06/04/2020
The Impact of COVID-19 on Flight Networks
As COVID-19 transmissions spread worldwide, governments have announced a...
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02/04/2020
Obstruction level detection of sewer videos using convolutional neural networks
Worldwide, sewer networks are designed to transport wastewater to a cent...
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11/26/2019
Random Forest as a Tumour Genetic Marker Extractor
Finding tumour genetic markers is essential to biomedicine due to their ...
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11/22/2019
Towards a Goal-oriented Agent-based Simulation framework for High-Performance Computing
Currently, agent-based simulation frameworks force the user to choose be...
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11/20/2019
MetH: A family of high-resolution and variable-shape image challenges
High-resolution and variable-shape images have not yet been properly add...
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11/08/2019
Feature discriminativity estimation in CNNs for transfer learning
The purpose of feature extraction on convolutional neural networks is to...
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12/21/2018
Adaptive Pattern Matching with Reinforcement Learning for Dynamic Graphs
Graph pattern matching algorithms to handle million-scale dynamic graphs...
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04/24/2018
A Visual Distance for WordNet
Measuring the distance between concepts is an important field of study o...
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07/24/2017
Full-Network Embedding in a Multimodal Embedding Pipeline
The current state-of-the-art for image annotation and image retrieval ta...
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07/24/2017
Building Graph Representations of Deep Vector Embeddings
Patterns stored within pre-trained deep neural networks compose large an...
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05/22/2017
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks
Transfer learning for feature extraction can be used to exploit deep rep...
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03/03/2017
On the Behavior of Convolutional Nets for Feature Extraction
Deep neural networks are representation learning techniques. During trai...
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11/02/2016
