With skeleton-based action recognition, it is crucial to recognize the dependencies among joints. However, current methods are not able capture relativity of various joints frames, which extremely helpful because parts body moving at same time. In order solve this problem, a new sequence segmentation attention network (SSAN) presented. The successive frames encoded in each segments that make up...

We present a Neural Network based Handwritten Text Recognition (HTR) model architecture that can be trained to recognize full pages of handwritten or printed text without image segmentation. Being on Image Sequence architecture, it extract in an and then sequence correctly imposing any constraints regarding orientation, layout size non-text. Further, also generate auxiliary markup related forma...

A computer program (RSITE) was developed which predicts the recognition sequence of a restriction endonuclease. The sizes of fragments experimentally determined on cleavage of a DNA of known sequence were input. Possible recognition sequences producing fragments of sizes matching those determined empirically were printed out. The program faithfully predicted the specificity of restriction enzym...

In the digital era, preserving old documents to prevent damage is a significant challenge. One solution this problem reconstruct damaged or lost using image processing and natural language technologies. This article discusses design of tool for correcting reconstructing writing in papers that can be implemented on mini PC. The uses state-of-the-art algorithms such as Convolutional Neural Networ...

As a practical application of Optical Character Recognition (OCR) for the digital situation, instrument recognition is significant to achieve automatic information management in real-industrial scenarios. However, different from normal task such as license plate recognition, CAPTCHA and handwritten digit multi-type instruments faces greater challenges due reading strings are variable-length wit...

This paper targets unsupervised skeleton-based action representation learning and proposes a new Hierarchical Contrast (HiCo) framework. Different from the existing contrastive-based solutions that typically represent an input skeleton sequence into instance-level features perform contrast holistically, our proposed HiCo represents multiple-level performs in hierarchical manner. Specifically, g...

Exposure to a repeating sequence of target stimuli in a speeded localization task can support both priming of sequence-consistent responses and recognition of sequence components. Here, a task is introduced in which measures of priming and recognition are obtained concurrently, and it is demonstrated that priming of sequence-consistent responses occurs even when test stimuli are not recognized....