Tomás Maul
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View article: Living with elephants: Deep learning models performance in examining Asian elephant (Elephas maximus) sounds from Sri Lanka and Malaysia with considerations for application
Living with elephants: Deep learning models performance in examining Asian elephant (Elephas maximus) sounds from Sri Lanka and Malaysia with considerations for application Open
View article: Enhancing Out-of-distribution Detection via Local-Image Set
Enhancing Out-of-distribution Detection via Local-Image Set Open
View article: Machine Learning-Enhanced Graphene/TiO2based Electrochemical Biosensor for Precise Discrimination of Dengue Virus Serotype IgG
Machine Learning-Enhanced Graphene/TiO2based Electrochemical Biosensor for Precise Discrimination of Dengue Virus Serotype IgG Open
View article: Antimatter Networks for Combating the Dying ReLU Problem
Antimatter Networks for Combating the Dying ReLU Problem Open
ReLU nodes are utilized commonly in neural networks as they look and act like linear functions while providing nonlinearity. In spite of addressing the vanishing gradient problem, they can lead to the dying ReLU problem which can be detrim…
View article: Exploring feature sparsity for out-of-distribution detection
Exploring feature sparsity for out-of-distribution detection Open
View article: Generative Design in the Built Environment
Generative Design in the Built Environment Open
View article: Can lies be faked? Comparing low-stakes and high-stakes deception video datasets from a Machine Learning perspective
Can lies be faked? Comparing low-stakes and high-stakes deception video datasets from a Machine Learning perspective Open
Despite the great impact of lies in human societies and a meager 54% human accuracy for Deception Detection (DD), Machine Learning systems that perform automated DD are still not viable for proper application in real-life settings due to d…
View article: Arthropodia-V1: Biodiversity Dataset for Semantic Segmentation, Quality Estimation, and Observation Extraction
Arthropodia-V1: Biodiversity Dataset for Semantic Segmentation, Quality Estimation, and Observation Extraction Open
View article: Enhancing Breast Cancer Histopathological Image Classification using Attention-Based High Order Covariance Pooling
Enhancing Breast Cancer Histopathological Image Classification using Attention-Based High Order Covariance Pooling Open
The type of cancer that affects female patients most frequently is breast cancer. Computer-aided diagnosis, these days, proves to be helpful for many diseases including breast cancer. Deep learning based approaches have yielded encouraging…
View article: Charging water load prediction for a thermal-energy-storage air-conditioner of a commercial building with a multilayer perceptron
Charging water load prediction for a thermal-energy-storage air-conditioner of a commercial building with a multilayer perceptron Open
This research focuses on the development of a machine learning model for predicting the water volume that needs to be chilled in Thermal-Energy-Storage-Air-Conditioning (TES-AC) systems. TES-AC technology uses thermal energy storage tanks …
View article: Effects of external weather on the water consumption of Thermal-Energy-Storage Air-Conditioning system
Effects of external weather on the water consumption of Thermal-Energy-Storage Air-Conditioning system Open
Thermal-Energy-Storage Air-Conditioning (TES-AC), a sustainable form of Air-Conditioning (AC) operates by storing thermal energy as chilled water when energy demand is low during nighttime. Later it uses the stored thermal energy during th…
View article: Charging Water Load Prediction for a Thermal-Energy-Storage Air-Conditioner of a Commercial Building with a Multilayer Perceptron
Charging Water Load Prediction for a Thermal-Energy-Storage Air-Conditioner of a Commercial Building with a Multilayer Perceptron Open
View article: Can lies be faked? Comparing low-stakes and high-stakes deception video datasets from a Machine Learning perspective
Can lies be faked? Comparing low-stakes and high-stakes deception video datasets from a Machine Learning perspective Open
Despite the great impact of lies in human societies and a meager 54% human accuracy for Deception Detection (DD), Machine Learning systems that perform automated DD are still not viable for proper application in real-life settings due to d…
View article: Application of deep learning in facility management and maintenance for heating, ventilation, and air conditioning
Application of deep learning in facility management and maintenance for heating, ventilation, and air conditioning Open
Despite the promising results of deep learning research, construction industry applications are still limited. Facility Management (FM) in construction has yet to take full advantage of the efficiency of deep learning techniques in daily o…
View article: Towards Idea Mining: Problem-Solution Phrase Extraction from Text
Towards Idea Mining: Problem-Solution Phrase Extraction from Text Open
View article: Effects of External Weather on the Water Consumption of Thermal-Energy-Storage Air-Conditioning System
Effects of External Weather on the Water Consumption of Thermal-Energy-Storage Air-Conditioning System Open
View article: Maker Education for Cultural Awareness With a Serious 3d Game Authoring Tool: Design Considerations
Maker Education for Cultural Awareness With a Serious 3d Game Authoring Tool: Design Considerations Open
View article: ARTIFICIAL INTELLIGENCE AND COMPUTER VISION – A MATCH MADE IN HEAVEN?
ARTIFICIAL INTELLIGENCE AND COMPUTER VISION – A MATCH MADE IN HEAVEN? Open
After becoming independent in 1957, Malaysia continued as an agricultural country but quickly grew into a manufacturing nation in a relatively short time. Literally from nowhere, the manufacturing sector now commands more than 38% of the n…
View article: AEGR: a simple approach to gradient reversal in autoencoders for network anomaly detection
AEGR: a simple approach to gradient reversal in autoencoders for network anomaly detection Open
View article: Balancing Accuracy and Latency in Multipath Neural Networks
Balancing Accuracy and Latency in Multipath Neural Networks Open
The growing capacity of neural networks has strongly contributed to their success at complex machine learning tasks and the computational demand of such large models has, in turn, stimulated a significant improvement in the hardware necess…
View article: An Empirical Study of Several Information Theoretic Based Feature Extraction Methods for Classifying High Dimensional Low Sample Size Data
An Empirical Study of Several Information Theoretic Based Feature Extraction Methods for Classifying High Dimensional Low Sample Size Data Open
A high dimensional low sample size (HDLSS) dataset typically contains many features but a limited number of samples. It is commonly found in domains such as microarray data and medical imaging. When sample size is small, the population pro…
View article: Towards a Universal Gating Network for Mixtures of Experts
Towards a Universal Gating Network for Mixtures of Experts Open
The combination and aggregation of knowledge from multiple neural networks can be commonly seen in the form of mixtures of experts. However, such combinations are usually done using networks trained on the same tasks, with little mention o…
View article: Path Capsule Networks
Path Capsule Networks Open
View article: Data Augmentation by AutoEncoders for Unsupervised Anomaly Detection
Data Augmentation by AutoEncoders for Unsupervised Anomaly Detection Open
This paper proposes an autoencoder (AE) that is used for improving the performance of once-class classifiers for the purpose of detecting anomalies. Traditional one-class classifiers (OCCs) perform poorly under certain conditions such as h…
View article: AEGR: A simple approach to gradient reversal in autoencoders for network anomaly detection
AEGR: A simple approach to gradient reversal in autoencoders for network anomaly detection Open
Anomaly detection is referred to as a process in which the aim is to detect data points that follow a different pattern from the majority of data points. Anomaly detection methods suffer from several well-known challenges that hinder their…
View article: Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic\n Information Balancing
Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic\n Information Balancing Open
Lifelong learning is a very important step toward realizing robust autonomous\nartificial agents. Neural networks are the main engine of deep learning, which\nis the current state-of-the-art technique in formulating adaptive artificial\nin…
View article: Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic Information Balancing
Reducing Catastrophic Forgetting in Modular Neural Networks by Dynamic Information Balancing Open
Lifelong learning is a very important step toward realizing robust autonomous artificial agents. Neural networks are the main engine of deep learning, which is the current state-of-the-art technique in formulating adaptive artificial intel…
View article: Detecting Point Outliers Using Prune-based Outlier Factor (PLOF)
Detecting Point Outliers Using Prune-based Outlier Factor (PLOF) Open
Outlier detection (also known as anomaly detection or deviation detection) is a process of detecting data points in which their patterns deviate significantly from others. It is common to have outliers in industry applications, which could…
View article: DATA AUGMENTATION APPROACHES FOR SATELLITE IMAGE SUPER-RESOLUTION
DATA AUGMENTATION APPROACHES FOR SATELLITE IMAGE SUPER-RESOLUTION Open
Data augmentation is a well known technique that is frequently used in machine learning tasks to increase the number of training instances and hence decrease model over-fitting. In this paper we propose a data augmentation technique that c…
View article: Weight Map Layer for Noise and Adversarial Attack Robustness
Weight Map Layer for Noise and Adversarial Attack Robustness Open
Convolutional neural networks (CNNs) are known for their good performance and generalization in vision-related tasks and have become state-of-the-art in both application and research-based domains. However, just like other neural network m…