45 Result(s)
within
Computer Science
Artificial Intelligence
M. **gliang
Chapter
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Chapter and Conference Paper
The Death Process in Italy Before and During the Covid-19 Pandemic: A Functional Compositional Approach
In this talk, based on [1], we propose a spatio-temporal analysis of daily death counts in Italy, collected by ISTAT (Italian Statistical Institute), in Italian provinces and municipalities. While in [1] the f...
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Chapter and Conference Paper
The Sixth Visual Object Tracking VOT2018 Challenge Results
The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers...
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Chapter and Conference Paper
Research on the Key Techniques of Semantic Mining of Information Digest in the Field of Agricultural Major Crops Based on Deep Learning
Nowadays application scopes of deep learning research in the machine learning subfield have been gradually expanded, mainly in the field of computer vision and natural language processing. However, in the latt...
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Chapter and Conference Paper
Automatic Airway Segmentation in Chest CT Using Convolutional Neural Networks
Segmentation of the airway tree from chest computed tomography (CT) images is critical for quantitative assessment of airway diseases including bronchiectasis and chronic obstructive pulmonary disease (COPD). ...
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Chapter and Conference Paper
AGIL: Learning Attention from Human for Visuomotor Tasks
When intelligent agents learn visuomotor behaviors from human demonstrations, they may benefit from knowing where the human is allocating visual attention, which can be inferred from their gaze. A wealth of in...
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Chapter and Conference Paper
Rough Set Rules Determine Disease Progressions in Different Groups of Parkinson’s Patients
Parkinson’s disease (PD) is the second after Alzheimer most popular neurodegenerative disease (ND). We do not have cure for both NDs. Therefore the purpose of our study was to predict results of different PD ...
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Chapter and Conference Paper
Identification of Regularities in CAD Part and Assembly Models
The identification of regular patterns of congruent features in CAD models can enrich the object representation by a set of higher level information, which can be exploited for the reuse of the part model. In ...
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Chapter and Conference Paper
Photoacoustic Imaging Paradigm Shift: Towards Using Vendor-Independent Ultrasound Scanners
Photoacoustic (PA) imaging requires channel data acquisition synchronized with a laser firing system. Unfortunately, the access to these channel data is only available on specialized research systems, and most...
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Chapter and Conference Paper
User Perceptions of a Virtual Human Over Mobile Video Chat Interactions
We believe that virtual humans, presented over video chat services, such as Skype, and delivered using smartphones, can be an effective way to deliver innovative applications where social interactions are impo...
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Chapter and Conference Paper
Discriminative Interpolation for Classification of Functional Data
The modus operandi for machine learning is to represent data as feature vectors and then proceed with training algorithms that seek to optimally partition the feature space
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Chapter and Conference Paper
Untangling Operator Monitoring Approaches When Designing Intelligent Adaptive Systems for Operational Environments
An Intelligent Adaptive System (IAS) is a synergy between an intelligent interface and adaptive automation technologies capable of context sensitive interaction with operators. A well-designed IAS should enabl...
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Chapter and Conference Paper
Towards Quantifying Interaction Networks in a Football Match
We present several novel methods quantifying dynamic interactions in simulated football games. These interactions are captured in directed networks that represent significant coupled dynamics, detected informa...
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Chapter and Conference Paper
Interestingness Prediction by Robust Learning to Rank
The problem of predicting image or video interestingness from their low-level feature representations has received increasing interest. As a highly subjective visual attribute, annotating the interestingness v...
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Chapter and Conference Paper
Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation
Most existing zero-shot learning approaches exploit transfer learning via an intermediate-level semantic representation such as visual attributes or semantic word vectors. Such a semantic representation is sha...
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Chapter and Conference Paper
Estimating Anatomically-Correct Reference Model for Craniomaxillofacial Deformity via Sparse Representation
The success of craniomaxillofacial (CMF) surgery depends not only on the surgical techniques, but also upon an accurate surgical planning. However, surgical planning for CMF surgery is challenging due to the a...
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Chapter and Conference Paper
Active Echo: A New Paradigm for Ultrasound Calibration
In ultrasound-guided medical procedures, accurate tracking of interventional tools with respect to the US probe is crucial to patient safety and clinical outcome. US probe tracking requires an unavoidable cali...
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Chapter and Conference Paper
Spá: A Web-Based Viewer for Text Mining in Evidence Based Medicine
Summarizing the evidence about medical interventions is an immense undertaking, in part because unstructured Portable Document Format (PDF) documents remain the main vehicle for disseminating scientific findin...
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Chapter and Conference Paper
Revisit Behavior in Social Media: The Phoenix-R Model and Discoveries
How many listens will an artist receive on a online radio? How about plays on a YouTube video? How many of these visits are new or returning users? Modeling and mining popularity dynamics of social activity ha...
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Chapter and Conference Paper
Routing with Dijkstra in Mobile Ad-Hoc Networks
It is important that robot teams have an effective communication infrastructure, especially for robots making rescue operations in debris areas. The robots making rescue operation in a large area of disaster a...
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Chapter and Conference Paper
Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model
We propose a probabilistic graphical model for predicting student attainment in web-based education. We empirically evaluate our model on a crowdsourced dataset with students and teachers; Teachers prepared le...
