Object-shape recognition from tactile images using a feed-forward neural network

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2012, Pages

  Khasnobish, Anwesha ^a   Jati, Arindam ^a   Singh, Garima ^a   Bhattacharyya, Saugat ^a   Konar, Amit ^a   Tibarewala, D N ^a   Kim, Eunjin ^b   Nagar, Atulya K ^c  

^a JADAVPUR UNIVERSITY   (India)

^b University of North Dakota   (United States)

^c LIVERPOOL HOPE UNIVERSITY   (United Kingdom)

Author keywords

edge detection; feed forward neural network; Friedman test; McNemar's test; Shape Recognition; tactile image

Indexed keywords

CLASSIFICATION ACCURACY; CLASSIFIER PERFORMANCE; CYLINDRICAL OBJECTS; FRIEDMAN TEST; HUMAN BODIES; HUMAN COMPUTER INTERFACES; K-NEAREST NEIGHBORS; LINEAR DISCRIMINANT ANALYSIS; LINEAR SUPPORT VECTOR MACHINES; MCNEMAR; MEAN CLASSIFICATION; NOISE POWER; OBJECT SHAPE; OBJECT SURFACE; PLANAR SURFACE; RADIAL BASIS FUNCTIONS; RECONSTRUCTED IMAGE; SENSE OF TOUCH; SENSORY SYSTEM; SHAPE RECOGNITION; SIGNAL POWER; SIGNAL TO NOISE; SNR VALUES; TACTILE IMAGES; TACTILE PRESSURE;

EDGE DETECTION; IMAGE RETRIEVAL; IMAGE SEGMENTATION; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SENSORY AIDS; SIGNAL TO NOISE RATIO; SUPPORT VECTOR MACHINES;

IMAGE RECONSTRUCTION;

EID: 84865082394     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2012.6252593     Document Type: Conference Paper

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