The increasing popularity of crowdsourcing platforms, i.e., Amazon Mechanical Turk, changes how datasets for supervised learning are built. In these cases, instead having labeled by one source (which is supposed to be an expert who provided the absolute gold standard), databases holding multiple annotators provided. However, most state-of-the-art methods devoted from experts assume that labeler...

This paper describes a neural network classifier for the 11000 chip, which optically reads the E13B font characters at the bottom of checks. The first layer of the neural network is a hardware linear classifier which recognizes the characters in this font . A second software neural layer is implemented on an inexpensive microprocessor to clean up the results of the first layer. The hardware lin...

To compensate the flaws of single neural network such as low classification precision and long training time as well as weak generalized ability etc, the paper proposes a novel ensemble neural classifier for stream turbine vibration fault diagnosis with improved PSO-based. The method fully utilizes the advantages of PSO, such as fast seeking speed and easily realizing mode etc, the integrated t...

This paper presents a method to fuse the information from motion segmentation with online adaptive neural classifier for robust object tracking. The motion segmentation with object classification identify new objects present in the video sequence. This information is used to initialize the online adaptive neural classifier which is learned to differentiate the object from its local background. ...

A new approach to intelligent gas sensor (IGS) design using a classifier based on adaptive resonance theory (ART) artificial neural network (ANN) is presented. Using published data of sensor arrays fabricated and characterised at our laboratory, we demonstrate excellent gas/odour identification performance of our classifier for a 4-gas, 4-sensor system to identify individual gas/odour. Since th...