Neuro-Fuzzy Computing System with the Capacity of Implementation on Memristor-Crossbar and Optimization-Free Hardware Training

In this paper, first we present a new explanation for the relation between logical circuits and artificial neural networks, logical circuits and fuzzy logic, and artificial neural networks and fuzzy inference systems. Then, based on these results, we propose a new neuro-fuzzy computing system which can effectively be implemented on the memristor-crossbar structure. One important feature of the proposed system is that its hardware can directly be trained using the Hebbian learning rule and without the need to any optimization. The system also has a very good capability to deal with huge number of input-out training data without facing problems like overtraining.Comment: 16 pages, 11 images, submitted to IEEE Trans. on Fuzzy system

Goal Detection in Soccer Video: Role-Based Events Detection Approach

Soccer video processing and analysis to find critical events such as occurrences of goal event have been one of the important issues and topics of active researches in recent years. In this paper, a new role-based framework is proposed for goal event detection in which the semantic structure of soccer game is used. Usually after a goal scene, the audiences’ and reporters’ sound intensity is increased, ball is sent back to the center and the camera may: zoom on Player, show audiences’ delighting, repeat the goal scene or display a combination of them. Thus, the occurrence of goal event will be detectable by analysis of sequences of above roles. The proposed framework in this paper consists of four main procedures: 1- detection of game’s critical events by using audio channel, 2- detection of shot boundary and shots classification, 3- selection of candidate events according to the type of shot and existence of goalmouth in the shot, 4- detection of restarting the game from the center of the field. A new method for shot classification is also presented in this framework. Finally, by applying the proposed method it was shown that the goal events detection has a good accuracy and the percentage of detection failure is also very low.DOI:http://dx.doi.org/10.11591/ijece.v4i6.637