In this paper we describe our current work on automatic continuous sign language recognition. We present an automatic sign language recognition system that is based on a large vocabulary speech recognition system and adopts many of the approaches that are conventionally applied in the recognition of spoken language. Furthermore, we present a set of freely available databases that can be used fo...

This paper outlines a concept of a continuous sign language translation system. The system consists of two main components. One of these is a video-based recognition tool, which aims for automatic signer dependent recognition of sign language sentences, based on a lexicon of 100 signs of German Sign Language. A single colour video camera is used for image recording. The recognition is based on ...

Sign language recognition is a difficult task, yet required for many applications in real-time speed. Using RGB cameras for recognition of sign languages is not very successful in practical situations and accurate 3D imaging requires expensive and complex instruments. With introduction of Time-of-Flight (ToF) depth cameras in recent years, it has become easier to scan the environment for accura...

With the growing trend in autonomous vehicles, accurate recognition of traffic signs has become crucial. This research focuses on use convolutional neural networks for sign classification, specifically utilizing pre-trained models ResNet50, DenseNet121, and VGG16. To enhance accuracy robustness model, authors implement an ensemble learning technique with majority voting, to combine predictions ...