Previous studies have highlighted the necessity for entity linking systems to capture the local entity-mention similarities and the global topical coherence. We introduce a novel framework based on convolutional neural networks and recurrent neural networks to simultaneously model the local and global features for entity linking. The proposed model benefits from the capacity of convolutional ne...

This paper is devoted to finger spelling recognition on the basis of images acquired by a single color camera. The recognition is realized on the basis of learned low-dimensional embeddings. The embeddings are calculated both by single as well as multiple siamese-based convolutional neural networks. We train classifiers operating on such features as well as convolutional neural networks operati...

Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase the size extent of neural recordings. Even so, interpretation this data requires considerable knowledge about nature representation often depends on manual operations. Decoding provides means to infer information content recordings but typically highly processed prior encoding scheme. Here,...

For the problem whether Graphic Processing Unit(GPU),the stream processor with high performance of floating— point computing is applicable to neural networks, this paper proposes the parallel recognition algorithm of Convolutional Neural Networks(CNNs).It adopts Compute Unified Device Architecture(CUDA)technology, definite the parallel data structures, and describes the mapping mechanism for co...