Recently, codes over some special finite rings especially chain rings have been studied. More recently, codes over finite non-chain rings have been also considered. Study on codes over such rings or rings in general is motivated by the existence of some special maps called Gray maps whose images give codes over fields. Quantum error-correcting (QEC) codes play a crucial role in protecting quantum ...

Visual place recognition is one of the essential and challenging problems in fields robotics. In this letter, we for first time explore use multi-modal fusion semantic visual modalities dynamics-invariant space to improve dynamic environments. We achieve by designing a novel deep learning architecture generate static segmentation recover image directly from corresponding image. then innovativel...

Two experiments on visual letter-matching have been widely cited in the literature as Indicating a role of acoustic codes in such tasks. Posner and Mitchell (1967) concluded that a visual code is sufficient to compare two identical letters (e.g.. AA), whereas a slower forming acoustic code is required to compare nonidentical letters, whether with the same name (e.g.. Aa) or with different names...

Due to explosive growth of visual content on the web, there is an emerging need of fast similarity search to efficiently exploit such enormous web contents from very large databases. Recently, hashing has become very popular for efficient nearest neighbor search in large scale applications. However, many traditional hashing methods learn the binary codes in a single shot or only employ a single...

The reading process of visual codes consists of two steps, localization and data decoding. This paper presents a novel method for QR code localization using deep rectifier neural networks, trained directly in the JPEG DCT domain, thus making image decompression unnecessary. This approach is efficient with respect to both storage and computation cost, being convenient, since camera hardware can ...

Neurophysiological studies have examined many aspects of neuronal activity in terms of neuronal codes and postulated roles for these codes in brain processing. There has been relatively little work, however, examining the relationship between different neuronal codes and the behavioural phenomena associated with cognitive processes. Here, predictions about reaction time distributions derived fr...

In recent years, a lot of attention has been devoted to efficient nearest neighbor search by means of similarity-preserving hashing. One of the plights of existing hashing techniques is the intrinsic trade-off between performance and computational complexity: while longer hash codes allow for lower false positive rates, it is very difficult to increase the embedding dimensionality without incur...

In this work, we firstly propose deep network models and learning algorithms for learning binary hash codes given image representations under both unsupervised and supervised manners. Then, by leveraging the powerful capacity of convolutional neural networks, we propose an end-to-end architecture which jointly learns to extract visual features and produce binary hash codes. Our novel network de...