2023 - Research.com Computer Science in Italy Leader Award
2004 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to graph based learning and matching techniques, and for service to IAPR.
His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Pattern recognition and Theoretical computer science. The concepts of his Pattern recognition study are interwoven with issues in Application domain, Graph edit distance, Graph and Clustering coefficient. His studies in Computer vision integrate themes in fields like Tree, False positive paradox and Robustness.
He interconnects Feature, Data mining, Field, Staining and Computer-aided diagnosis in the investigation of issues within Pattern recognition. The Theoretical computer science study combines topics in areas such as Induced subgraph isomorphism problem, Graph isomorphism, 3-dimensional matching and Matching, Algorithm. His work deals with themes such as Indifference graph and Cograph, Pathwidth, which intersect with Induced subgraph isomorphism problem.
Mario Vento mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Pattern recognition and Machine learning. His Artificial intelligence study frequently draws connections to adjacent fields such as Data mining. His Computer vision research includes elements of Process and Set.
His study looks at the relationship between Pattern recognition and fields such as Graph, as well as how they intersect with chemical problems. His Theoretical computer science study combines topics in areas such as Graph isomorphism, Algorithm and Induced subgraph isomorphism problem. His Pattern recognition research integrates issues from Field, Staining and Natural language processing.
Mario Vento mainly focuses on Artificial intelligence, Deep learning, Convolutional neural network, Subgraph isomorphism problem and Pattern recognition. His Artificial intelligence research incorporates elements of Machine learning and Computer vision. His Deep learning study also includes
His study in Convolutional neural network is interdisciplinary in nature, drawing from both Event, Field and Benchmark. His Subgraph isomorphism problem study combines topics from a wide range of disciplines, such as Algorithm, Parallel algorithm and Parallelism. His work on Pattern recognition as part of general Pattern recognition study is frequently connected to Audio analyzer, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
The scientist’s investigation covers issues in Artificial intelligence, Subgraph isomorphism problem, Video tracking, Face and Host. As a part of the same scientific family, Mario Vento mostly works in the field of Artificial intelligence, focusing on Pattern recognition and, on occasion, Robustness. The study incorporates disciplines such as Matching, Algorithm, Graph database and Theoretical computer science in addition to Subgraph isomorphism problem.
His studies deal with areas such as Parallel algorithm, Parallelism and Induced subgraph isomorphism problem as well as Theoretical computer science. His work carried out in the field of Video tracking brings together such families of science as Object detection, Perspective and Smart system. His Face research focuses on State and how it relates to Exploit.
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THIRTY YEARS OF GRAPH MATCHING IN PATTERN RECOGNITION
Donatello Conte;Pasquale Foggia;Carlo Sansone;Mario Vento.
International Journal of Pattern Recognition and Artificial Intelligence (2004)
A (sub)graph isomorphism algorithm for matching large graphs
L.P. Cordella;P. Foggia;C. Sansone;M. Vento.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)
Trainable COSFIRE filters for vessel delineation with application to retinal images
George Azzopardi;Nicola Strisciuglio;Mario Vento;Nicolai Petkov.
Medical Image Analysis (2015)
An Improved Algorithm for Matching Large Graphs
L. P. Cordella;P. Foggia;C. Sansone;M. Vento.
GRAPH MATCHING AND LEARNING IN PATTERN RECOGNITION IN THE LAST 10 YEARS
Pasquale Foggia;Gennaro Percannella;Mario Vento.
International Journal of Pattern Recognition and Artificial Intelligence (2014)
Performance evaluation of the VF graph matching algorithm
L.P. Cordella;P. Foggia;C. Sansone;M. Vento.
international conference on image analysis and processing (1999)
Benchmarking HEp-2 Cells Classification Methods
Pasquale Foggia;Gennaro Percannella;Paolo Soda;Mario Vento.
IEEE Transactions on Medical Imaging (2013)
A Performance Comparison of Five Algorithms for Graph Isomorphism
P. Foggia;C.Sansone;M. Vento.
To reject or not to reject: that is the question-an answer in case of neural classifiers
C. De Stefano;C. Sansone;M. Vento.
systems man and cybernetics (2000)
Real-Time Fire Detection for Video-Surveillance Applications Using a Combination of Experts Based on Color, Shape, and Motion
Pasquale Foggia;Alessia Saggese;Mario Vento.
IEEE Transactions on Circuits and Systems for Video Technology (2015)
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