2023 - Research.com Computer Science in Italy Leader Award
Artificial intelligence, Machine learning, Support vector machine, Discriminative model and Pattern recognition are her primary areas of study. Her work on Artificial intelligence is being expanded to include thematically relevant topics such as Computer vision. Her work deals with themes such as Classifier and Video tracking, which intersect with Machine learning.
As part of one scientific family, Barbara Caputo deals mainly with the area of Support vector machine, narrowing it down to issues related to the Material classification, and often Markov random field and Scale variation. While the research belongs to areas of Discriminative model, Barbara Caputo spends her time largely on the problem of Image retrieval, intersecting her research to questions surrounding Cognitive models of information retrieval. Her Pattern recognition research includes themes of Contextual image classification and 3D single-object recognition.
Barbara Caputo mostly deals with Artificial intelligence, Machine learning, Pattern recognition, Support vector machine and Robot. Her research links Computer vision with Artificial intelligence. The Machine learning study combines topics in areas such as Classifier, Segmentation and Benchmark.
The Feature extraction and Kernel method research she does as part of her general Pattern recognition study is frequently linked to other disciplines of science, such as Domain adaptation, therefore creating a link between diverse domains of science. Her biological study spans a wide range of topics, including Kernel and Automatic image annotation. Her Robot research incorporates elements of Robustness and Human–computer interaction.
Barbara Caputo focuses on Artificial intelligence, Machine learning, Deep learning, Benchmark and Human–computer interaction. In her research, she undertakes multidisciplinary study on Artificial intelligence and Domain adaptation. Barbara Caputo regularly ties together related areas like Image in her Machine learning studies.
Her Benchmark research is multidisciplinary, incorporating elements of Isolation and Object detection. Her research integrates issues of Psychophysics and Eye tracking in her study of Human–computer interaction. Her Adaptation study which covers Feature that intersects with Pattern recognition.
Her main research concerns Artificial intelligence, Cognitive neuroscience of visual object recognition, Human–computer interaction, Machine learning and Deep learning. Barbara Caputo incorporates Artificial intelligence and Domain adaptation in her studies. Her Cognitive neuroscience of visual object recognition research is multidisciplinary, relying on both Supervised learning and Unsupervised learning.
Her studies in Human–computer interaction integrate themes in fields like Eye tracking and Gaze. Her work in Categorization addresses issues such as RGB color model, which are connected to fields such as Relation and Pattern recognition. Her Visualization research is multidisciplinary, incorporating perspectives in Data modeling, Data point and Feature.
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Recognizing human actions: a local SVM approach
C. Schuldt;I. Laptev;B. Caputo.
international conference on pattern recognition (2004)
Electromyography data for non-invasive naturally-controlled robotic hand prostheses
Manfredo Atzori;Arjan Gijsberts;Claudio Castellini;Barbara Caputo.
Scientific Data (2014)
On the Significance of Real‐World Conditions for Material Classification
Eric Hayman;Barbara Caputo;Mario Fritz;Jan Olof Eklundh.
european conference on computer vision (2004)
Class-specific material categorisation
B. Caputo;E. Hayman;P. Mallikarjuna.
international conference on computer vision (2005)
Domain Generalization by Solving Jigsaw Puzzles
Fabio M. Carlucci;Antonio D'Innocente;Silvia Bucci;Barbara Caputo.
computer vision and pattern recognition (2019)
Local velocity-adapted motion events for spatio-temporal recognition
Ivan Laptev;Barbara Caputo;Christian Schüldt;Tony Lindeberg.
Computer Vision and Image Understanding (2007)
Multi-modal Semantic Place Classification
A. Pronobis;O. Martínez Mozos;B. Caputo;P. Jensfelt.
The International Journal of Robotics Research (2010)
Safety in numbers: Learning categories from few examples with multi model knowledge transfer
Tatiana Tommasi;Francesco Orabona;Barbara Caputo.
computer vision and pattern recognition (2010)
AutoDIAL: Automatic Domain Alignment Layers
Fabio Maria Cariucci;Lorenzo Porzi;Barbara Caputo;Elisa Ricci.
international conference on computer vision (2017)
ImageCLEF: Experimental Evaluation in Visual Information Retrieval
Henning Mller;Paul Clough;Thomas Deselaers;Barbara Caputo.
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