A large portion of South Africa’s elephant population can be found on small wildlife reserves. When confined to enclosed reserves the elephant densities are much higher than observed in the wild. The large nutritional demands and destructive foraging behavior of elephants threaten rare species of vegetation. If conservation management is to protect threatened species of vegetation, knowing how ...

We present recent work on improving the performance of automated speech recognizers by using additional visual in formation Lip Speechreading achieving error reduction of up to This paper focuses on di erent methods of combining the visual and acoustic data to improve the recognition performance We show this on an extension of an existing state of the art speech recognition system a modular MS ...

In this paper we present an algorithm for recogniz ing walking pedestrians in sequences of color images taken from a moving camera The recognition is based on the characteristic motion of the legs of a pedestrian walking parallel to the image plane Each image is seg mented into region like image parts by clustering pixels in a combined color position feature space The pro posed clustering techn...

In this paper we show how recognition perfor-mance in automated speech perception can be significantlyimproved by additional Lipreading, so called “speech-read-ing”. We show this on an extension of an existing state-of-the-art speech recognition system, a modular MS-TDNN. Theacoustic and visual speech data is preclassified in two sepa-rate front-end phoneme TDNNs and com...

This paper presents a time delay neural network (TDNN) model designed for the prediction of nitrogen oxides (NO x) and carbon monoxide (CO) emissions from a fossil fuel power plant. NO x and CO emissions of the plant are determined as a function of other related time-series such as air ow rates and oxygen levels that are measured during the system operation. Correlation analysis is performed on...

We propose a new recognition model called Concurrent Neural Networks (CNN), representing a winner-takes-all collection of neural networks. Each network of the system is trained individually to provide best results for one class only. We have applied the above model for the task of speaker recognition. We performed distinct speaker recognition experiments using three variants of basic components...

Recurrent neural network architectures have been shown to efficiently model long term temporal dependencies between acoustic events. However the training time of recurrent networks is higher than feedforward networks due to the sequential nature of the learning algorithm. In this paper we propose a time delay neural network architecture which models long term temporal dependencies with training...

Handwriting recognition is an interesting part in pattern recognition field. In the last decade, several approaches are focused on online handwriting recognition because the very rapid growth of new technologies in the field of data entry. In this paper, we propose a new system for online Arabic handwriting recognition based on beta-elliptic model which allow to segment the trajectory into segm...

Several improvements in the Back-Propagation procedure are proposed to increase training speed, and we discuss their limitations with respect to generalization. performance. The error surface is modeled to avoid local minima and flat areas. The synaptic weights are updated as often as possible. Both the step size and the momentum are dynamically scaled to the largest possible values that do not...