Antonio Liotta
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View article: An experimental comparison of deep learning models for pneumonia classification from chest X-ray images
An experimental comparison of deep learning models for pneumonia classification from chest X-ray images Open
View article: Time Series Gaps Filling based on Heterogeneous Sensor Data Fusion
Time Series Gaps Filling based on Heterogeneous Sensor Data Fusion Open
View article: Feature-Level Uncertainty Response Analysis in Multi-Sensor Deep Learning Models
Feature-Level Uncertainty Response Analysis in Multi-Sensor Deep Learning Models Open
View article: An Innovative Approach for Calibrating Hydrological Surrogate Deep Learning Models
An Innovative Approach for Calibrating Hydrological Surrogate Deep Learning Models Open
Developing data-driven models for spatiotemporal hydrological prediction presents challenges in managing complexity, capturing fine spatial and temporal resolution, and ensuring model resilience across diverse regions. This study introduce…
View article: A comparative study of neural network pruning strategies for industrial applications
A comparative study of neural network pruning strategies for industrial applications Open
Introduction In recent years, Deep Learning (DL) and Artificial Neural Networks (ANNs) have transformed industrial applications by providing automation in complex tasks such as anomaly detection and predictive maintenance. However, traditi…
View article: GResilience: Decision-Making Policies for Trading Off Greenness and Resilience in Online Collaborative AI Systems
GResilience: Decision-Making Policies for Trading Off Greenness and Resilience in Online Collaborative AI Systems Open
Problem: An Online Collaborative AI System (OL-CAIS) learns online from human collaboration to achieve a common goal. It may be subjected to environmental events that disrupt the system’s decision-making policies, resulting in performance …
View article: A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Image Anomaly Detection
A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Image Anomaly Detection Open
In the advancement of industrial informatization, unsupervised anomaly detection technology effectively overcomes the scarcity of abnormal samples and significantly enhances the automation and reliability of smart manufacturing. As an impo…
View article: Comparative study of deep learning techniques for DeepFake video detection
Comparative study of deep learning techniques for DeepFake video detection Open
Deep learning addresses a wide range of complex challenges, spanning from computer vision to data analytics. It is also employed to develop softwares that pose threats to privacy and security. To develop a DeepFake video, an individual in …
View article: Short-Term Forecasting of Non-Stationary Time Series
Short-Term Forecasting of Non-Stationary Time Series Open
Forecasting climate events is crucial for mitigating and managing risks related to climate change; however, the problem of non-stationarity in time series (NTS) arises, making it difficult to capture and model the underlying trends. This t…
View article: Worthiness Benchmark: A novel concept for analyzing binary classification evaluation metrics
Worthiness Benchmark: A novel concept for analyzing binary classification evaluation metrics Open
Binary classification deals with identifying whether elements belong to one of two possible categories. Various metrics exist to evaluate the performance of such classification systems. It is important to study and contrast these metrics t…
View article: On the sensitivity of centrality metrics
On the sensitivity of centrality metrics Open
Despite the huge importance that the centrality metrics have in understanding the topology of a network, too little is known about the effects that small alterations in the topology of the input graph induce in the norm of the vector that …
View article: Modeling Resilience of Collaborative AI Systems
Modeling Resilience of Collaborative AI Systems Open
A Collaborative Artificial Intelligence System (CAIS) performs actions in collaboration with the human to achieve a common goal. CAISs can use a trained AI model to control human-system interaction, or they can use human interaction to dyn…
View article: Hybrid learning strategies for multivariate time series forecasting of network quality metrics
Hybrid learning strategies for multivariate time series forecasting of network quality metrics Open
This work addresses the challenge of forecasting temporal metrics that characterize cellular traffic behavior. The ultimate goal is to provide network operators with a valuable tool for modeling mobile network traffic and optimizing connec…
View article: Modeling Resilience of Collaborative AI Systems
Modeling Resilience of Collaborative AI Systems Open
A Collaborative Artificial Intelligence System (CAIS) performs actions in collaboration with the human to achieve a common goal. CAISs can use a trained AI model to control human-system interaction, or they can use human interaction to dyn…
View article: Worthiness Benchmark: A Novel Concept for Analyzing Binary Classification Evaluation Metrics
Worthiness Benchmark: A Novel Concept for Analyzing Binary Classification Evaluation Metrics Open
View article: Deep Learning Based Multi Pose Human Face Matching System
Deep Learning Based Multi Pose Human Face Matching System Open
Current techniques for multi-pose human face matching yield suboptimal outcomes because of the intricate nature of pose equalization and face rotation. Deep learning models, such as YOLO-V5, etc., that have been proposed to tackle these co…
View article: A Survey on Rgb, 3d, and Multimodal Approaches for Unsupervised Industrial Anomaly Detection
A Survey on Rgb, 3d, and Multimodal Approaches for Unsupervised Industrial Anomaly Detection Open
View article: Smarter Grid in the 5G Era: Integrating the Internet of Things With a Cyber-Physical System
Smarter Grid in the 5G Era: Integrating the Internet of Things With a Cyber-Physical System Open
The Smart Grid, a fusion of digital technologies and advanced communication methods, enables the transformation of power distribution, transmission, and generation by responding to fluctuations in electricity consumption. Conventional elec…
View article: Multivariate Time Series Characterization and Forecasting of VoIP Traffic in Real Mobile Networks
Multivariate Time Series Characterization and Forecasting of VoIP Traffic in Real Mobile Networks Open
Predicting the behavior of real-time traffic (e.g., VoIP) in mobility\nscenarios could help the operators to better plan their network infrastructures\nand to optimize the allocation of resources. Accordingly, in this work the\nauthors pro…
View article: Downscaling Fusion Model for CMIP5 Rainfall Projection under RCP Scenarios: The Case of Trentino-Alto Adige
Downscaling Fusion Model for CMIP5 Rainfall Projection under RCP Scenarios: The Case of Trentino-Alto Adige Open
Climate parameter projections obtained by global and regional models (GCM and RCM, respectively) offer a challenge to many researchers in terms of controlling the quality of the outcome data using several scales. In the literature, the pro…
View article: Edge-Enhanced QoS Aware Compression Learning for Sustainable Data Stream Analytics
Edge-Enhanced QoS Aware Compression Learning for Sustainable Data Stream Analytics Open
\nAbstract—In conventional cloud systems, large volumes of data streams are sent to the data centres for monitoring, storage, and\nanalytics. However, migrating all the data to the cloud is often not feasible due to cost, privacy, and perf…
View article: GResilience: Trading Off Between the Greenness and the Resilience of Collaborative AI Systems
GResilience: Trading Off Between the Greenness and the Resilience of Collaborative AI Systems Open
View article: E-MPSPNet: Ice–Water SAR Scene Segmentation Based on Multi-Scale Semantic Features and Edge Supervision
E-MPSPNet: Ice–Water SAR Scene Segmentation Based on Multi-Scale Semantic Features and Edge Supervision Open
Distinguishing sea ice and water is crucial for safe navigation and carrying out offshore activities in ice zones. However, due to the complexity and dynamics of the ice–water boundary, it is difficult for many deep learning-based segmenta…
View article: Covert Network Construction, Disruption, and Resilience: A Survey
Covert Network Construction, Disruption, and Resilience: A Survey Open
Covert networks refer to criminal organizations that operate outside the boundaries of the law; they can be mainly classified as terrorist networks and criminal networks. We consider how Social Network Analysis (SNA) is used to analyze suc…
View article: Computer-aided diagnosis for breast cancer classification using deep neural networks and transfer learning
Computer-aided diagnosis for breast cancer classification using deep neural networks and transfer learning Open
Our proposed method provides the best average accuracy for binary classification of benign or malignant cancer cases of 99.7%, 97.66%, and 96.94% for ResNet, InceptionV3Net, and ShuffleNet, respectively. Average accuracies for multi-class …
View article: A Novel Interannual Rainfall Runoff Equation Derived from Ol’Dekop’s Model Using Artificial Neural Networks
A Novel Interannual Rainfall Runoff Equation Derived from Ol’Dekop’s Model Using Artificial Neural Networks Open
In water resources management, modeling water balance factors is necessary to control dams, agriculture, irrigation, and also to provide water supply for drinking and industries. Generally, conceptual and physical models present challenges…
View article: A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff
A Hybrid Water Balance Machine Learning Model to Estimate Inter-Annual Rainfall-Runoff Open
Watershed climatic diversity poses a hard problem when it comes to finding suitable models to estimate inter-annual rainfall runoff (IARR). In this work, a hybrid model (dubbed MR-CART) is proposed, based on a combination of MR (multiple r…
View article: Network Connectivity Under a Probabilistic Node Failure Model
Network Connectivity Under a Probabilistic Node Failure Model Open
Node-removal processes are generally used to test network robustness against failures, verify the strength of a power grid, or contain fake news. Yet, a node-removal task is typically assumed to always be successful, whilst we argue that t…
View article: A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances
A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances Open
Affective computing plays a key role in human-computer interactions, entertainment, teaching, safe driving, and multimedia integration. Major breakthroughs have been made recently in the areas of affective computing (i.e., emotion recognit…
View article: Influence Maximisation with Budget Constraints and Node Fragility
Influence Maximisation with Budget Constraints and Node Fragility Open