AIMC Topic: Algorithms

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Collaborative Active Visual Recognition from Crowds: A Distributed Ensemble Approach.

IEEE transactions on pattern analysis and machine intelligence
Active learning is an effective way of engaging users to interactively train models for visual recognition more efficiently. The vast majority of previous works focused on active learning with a single human oracle. The problem of active learning wit...

Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems.

Journal of neural engineering
OBJECTIVE: This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandw...

Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy.

Journal of medical Internet research
BACKGROUND: Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor's activity for the purposes of quality assurance, safety, and continuing professional development.

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PloS one
Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identi...

Swarm Robots Search for Multiple Targets Based on an Improved Grouping Strategy.

IEEE/ACM transactions on computational biology and bioinformatics
Swarm robots search for multiple targets in collaboration in unknown environments has been addressed in this paper. An improved grouping strategy based on constriction factors Particle Swarm Optimization is proposed. Robots are grouped under this str...

Overcoming catastrophic forgetting in neural networks.

Proceedings of the National Academy of Sciences of the United States of America
The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature ...

SILVA, RDP, Greengenes, NCBI and OTT - how do these taxonomies compare?

BMC genomics
BACKGROUND: A key step in microbiome sequencing analysis is read assignment to taxonomic units. This is often performed using one of four taxonomic classifications, namely SILVA, RDP, Greengenes or NCBI. It is unclear how similar these are and how to...

Regularized Speaker Adaptation of KL-HMM for Dysarthric Speech Recognition.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper addresses the problem of recognizing the speech uttered by patients with dysarthria, which is a motor speech disorder impeding the physical production of speech. Patients with dysarthria have articulatory limitation, and therefore, they of...

Improving zero-training brain-computer interfaces by mixing model estimators.

Journal of neural engineering
OBJECTIVE: Brain-computer interfaces (BCI) based on event-related potentials (ERP) incorporate a decoder to classify recorded brain signals and subsequently select a control signal that drives a computer application. Standard supervised BCI decoders ...

Online Classification of Contaminants Based on Multi-Classification Support Vector Machine Using Conventional Water Quality Sensors.

Sensors (Basel, Switzerland)
Water quality early warning system is mainly used to detect deliberate or accidental water pollution events in water distribution systems. Identifying the types of pollutants is necessary after detecting the presence of pollutants to provide warning ...