Wenhan Zhang
Affiliations:- Gyrfalcon Technology Inc., Milpitas, CA, USA
According to our database1,
Wenhan Zhang
authored at least 12 papers
between 2018 and 2019.
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Bibliography
2019
System Demo for Transfer Learning across Vision and Text using Domain Specific CNN Accelerator for On-Device NLP Applications.
CoRR, 2019
SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models.
CoRR, 2019
2-bit Model Compression of Deep Convolutional Neural Network on ASIC Engine for Image Retrieval.
CoRR, 2019
SuperTML: Two-Dimensional Word Embedding and Transfer Learning Using ImageNet Pretrained CNN Models for the Classifications on Tabular Data.
CoRR, 2019
Proceedings of the 8th International Workshop on Big Data, 2019
System Demonstration of MRAM Co-designed Processing-in-Memory CNN Accelerator for Mobile and IoT Applications.
Proceedings of the 8th International Workshop on Big Data, 2019
On-device Chatbot System using SuperChat Method on Raspberry Pi and CNN Domain Specific Accelerator.
Proceedings of the 8th International Workshop on Big Data, 2019
Demonstration of Applications in Computer Vision and NLP on Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt.
Proceedings of the IEEE International Conference on Multimedia & Expo Workshops, 2019
SuperTML: Two-Dimensional Word Embedding for the Precognition on Structured Tabular Data.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019
Squared English Word: A Method of Generating Glyph to Use Super Characters for Sentiment Analysis.
Proceedings of the 2nd Workshop on Affective Content Analysis (AffCon 2019) co-located with Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), 2019
2018
Super Characters: A Conversion from Sentiment Classification to Image Classification.
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, 2018
Ultra Power-Efficient CNN Domain Specific Accelerator With 9.3TOPS/Watt for Mobile and Embedded Applications.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018