13 citations · 43 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
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.…
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…
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…
Squared English Word: A Method of Generating Glyph to Use Super Characters for Sentiment Analysis
Baohua Sun, Lin Yang, Catherine Chi +2
The Super Characters method addresses sentiment analysis problems by first converting the input text into images and then applying 2D-CNN models to classify the sentiment. It achie…