46 Result(s)
within
English
Computer Science
Information Systems Applications (incl. Internet)
Pattern Recognition
M. **gliang
Conference Paper
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Chapter and Conference Paper
Deep Learning for Accurate Corner Detection in Computer Vision-Based Inspection
This paper describes application of deep learning for accurate detection of corner points in images and its application for an inspection system developed for the worker training and assessment. In our local b...
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Chapter and Conference Paper
VisDrone-MOT2020: The Vision Meets Drone Multiple Object Tracking Challenge Results
The Vision Meets Drone (VisDrone2020) Multiple Object Tracking (MOT) is the third annual UAV MOT tracking evaluation activity organized by the VisDrone team, in conjunction with European Conference on Computer...
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Chapter and Conference Paper
Fiber Tracking in Traumatic Brain Injury: Comparison of 9 Tractography Algorithms
Traumatic brain injury (TBI) can cause widespread and long-lasting damage to white matter. Diffusion weighted imaging methods are uniquely sensitive to this disruption. Even so, traumatic injury often disrupts...
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Chapter and Conference Paper
Exploring the Long Tail of Social Media Tags
There are millions of users who tag multimedia content, generating a large vocabulary of tags. Some tags are frequent, while other tags are rarely used following a long tail distribution. For frequent tags, mo...
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Chapter and Conference Paper
Hyperalignment of Multi-subject fMRI Data by Synchronized Projections
Group analysis of fMRI data via multivariate pattern methods requires accurate alignments between neuronal activities of different subjects in order to attain competitive inter-subject classification rates. Hy...
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Chapter and Conference Paper
Class-Driven Color Transformation for Semantic Labeling
We propose a novel class-driven color transformation aimed at semantic labeling. In contrast with other approaches elsewhere in the literature, our approach is a supervised one employing class information to l...
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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
A Straightforward Implementation of a GPU-accelerated ELM in R with NVIDIA Graphic Cards
General purpose computing on graphics processing units (GPGPU) is a promising technique to cope with nowadays arising computational challenges due to the suitability of GPUs for parallel processing. Several li...
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Chapter and Conference Paper
Identification of Novel c-Yes Kinase Inhibitors
c-Yes is a member of Src tyrosine kinase family and it is over expressed in human colorectal cancer cells. c-Yes tyrosine kinase is an attractive target due to its inhibition controls colon tumorigenesis, meta...
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Chapter and Conference Paper
A 3D Tracker for Ground-Moving Objects
Multi-object tracking is a major area of research because of its wide application scope. In this paper we describe a set of improvements, toward video surveillance context, to the multi-object tracker proposed...
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Chapter and Conference Paper
An Adaptive Information Retrieval System for Efficient Web Searching
Stemming algorithms (stemmers) are used to convert the words to their root form (stem), this process is used in the pre-processing stage of the Information Retrieval Systems. The Stemmers affect the indexing t...
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Chapter and Conference Paper
Concept Recommendation System for Cloud Services Advertisement
Cloud computing is a major trend in Information Technology (IT), which has witnessed high adaption rate for cloud solutions. Software-as-a-Service (SaaS) providers compete to address nearly every business and ...
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Chapter and Conference Paper
Supervised Learning for the Neurosurgery Intensive Care Unit Using Single-Layer Perceptron Classifiers
In the continuing goal to merge the fields of computational neuroscience with medical based neurodiagnostic clinical research this paper presents advancements on machine learning Big Electroencephalogram (EEG)...
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Chapter and Conference Paper
A Computer Assisted Planning System for the Placement of sEEG Electrodes in the Treatment of Epilepsy
Approximately 20–30% of patients with focal epilepsy are medically refractory and may be candidates for curative surgery. Stereo EEG is the placement of multiple depth electrodes into the brain to record seizu...
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Chapter and Conference Paper
Are Some Brain Injury Patients Improving More Than Others?
Predicting the evolution of individuals is a rather new mining task with applications in medicine. Medical researchers are interested in the progress of a disease and in the evolution of individuals subjected ...
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Chapter and Conference Paper
Cosine Distance Metric Learning for Speaker Verification Using Large Margin Nearest Neighbor Method
In this paper, a novel cosine similarity metric learning based on large margin nearest neighborhood (LMNN) is proposed for an i-vector based speaker verification system. Generally, in an i-vector based speaker...
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Chapter and Conference Paper
Queries Based Workload Management System for the Cloud Environment
Workload management for concurrent queries is one of the challenging aspects of executing queries over the cloud computing environment. The core problem is to manage any unpredictable load imbalance with respe...
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Chapter and Conference Paper
Future Prospects of Human Interaction with Artificial Autonomous Systems
The growing complexity of intelligent systems and technologies raises questions concerning their interaction with human intelligence. The loss of an ability to control artificial intelligent and autonomous dec...
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Chapter and Conference Paper
A Parsing Approach to SAT
We present a parsing approach to address the problem of propositional satisfiability (SAT). We use a very simple translation from formulae in conjunctive normal form (CNF) to strings to be parsed by an Earley ...
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Chapter and Conference Paper
A Computationally and Cognitively Plausible Model of Supervised and Unsupervised Learning
Both empirical and mathematical demonstrations of the importance of chance-corrected measures are discussed, and a new model of learning is proposed based on empirical psychological results on association lear...
