A general approach to connected-component labeling for arbitrary image representations
Journal of the ACM (JACM)
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Efficient algorithms for mining outliers from large data sets
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Digital Image Processing
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
Multi-class pattern classification using neural networks
Pattern Recognition
Neural networks for mobile robot navigation: a survey
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Adaptive on-line neural network retraining for real life multimodal emotion recognition
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Neural networks for classification: a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Adaptive thresholding by variational method
IEEE Transactions on Image Processing
IEEE Transactions on Neural Networks
Face recognition with radial basis function (RBF) neural networks
IEEE Transactions on Neural Networks
A flexible edge matching technique for object detection in dynamic environment
Applied Intelligence
A multi-threshold segmentation approach based on Artificial Bee Colony optimization
Applied Intelligence
Acquisition of object pose from barcode for robot manipulation
SIMPAR'12 Proceedings of the Third international conference on Simulation, Modeling, and Programming for Autonomous Robots
Multi-circle detection on images inspired by collective animal behavior
Applied Intelligence
Accelerating FCM neural network classifier using graphics processing units with CUDA
Applied Intelligence
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In this paper, we address object recognition for a mobile robot which is deployed in a multistory building. To move to another floor, a mobile robot should recognize various objects related to an elevator, e.g., elevator control, call buttons, and LED displays. To this end, we propose a neural network based retrainable framework for object recognition, which consists of four components--preprocessing, binary classification, object identification, and outlier rejection. The binary classifier, a key component of our system, is a neural network that can be retrained, the motivation of which is to adapt to varying environments, especially with illuminations. Without incurring any extra process to prepare new training samples for retraining, they are freely obtained as a result of the outlier rejection component, being extracted on-line. To realize a practical system, we adopt a parallel architecture integrating both recognition and retraining processes for seamless object recognition, and furthermore detect and cope with the deterioration of a retrained neural network to ensure high reliability. We demonstrate the positive effect of retraining on the object recognition performance by conducting experiments over hundreds of images obtained in daytime and nighttime.