most citedSquared English Word: A Method of Generating Glyph to Use Super Characters for Sentiment Analysis

13 citations · 43 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20202 cited

SuperOCR: A Conversion from Optical Character Recognition to Image Captioning

Baohua Sun, Michael Lin, Hao Sha +1

Optical Character Recognition (OCR) has many real world applications. The existing methods normally detect where the characters are, and then recognize the character for each detec…

cs.CL20204 cited

Multi-modal Sentiment Analysis using Super Characters Method on Low-power CNN Accelerator Device

Baohua Sun, Lin Yang, Hao Sha +1

Recent years NLP research has witnessed the record-breaking accuracy improvement by DNN models. However, power consumption is one of the practical concerns for deploying NLP system…

cs.CL20195 cited

System Demo for Transfer Learning across Vision and Text using Domain Specific CNN Accelerator for On-Device NLP Applications

Baohua Sun, Lin Yang, Michael Lin +4

Power-efficient CNN Domain Specific Accelerator (CNN-DSA) chips are currently available for wide use in mobile devices. These chips are mainly used in computer vision applications.…

cs.CL20194 cited

SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding

Baohua Sun, Lin Yang, Michael Lin +4

Language and vision are processed as two different modal in current work for image captioning. However, recent work on Super Characters method shows the effectiveness of two-dimens…

cs.CL20196 cited

SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models

Baohua Sun, Lin Yang, Michael Lin +4

The recent work of Super Characters method using two-dimensional word embedding achieved state-of-the-art results in text classification tasks, showcasing the promise of this new a…

cs.CV20199 cited

SuperTML: Two-Dimensional Word Embedding for the Precognition on Structured Tabular Data

Baohua Sun, Lin Yang, Wenhan Zhang +4

Tabular data is the most commonly used form of data in industry. Gradient Boosting Trees, Support Vector Machine, Random Forest, and Logistic Regression are typically used for clas…