Networking retinomorphic sensor with memristive crossbar for brain-inspired visual perception     

Shuang Wang  Chen-Yu Wang  Pengfei Wang  Cong Wang  Zhu-An Li  Chen Pan  Yitong Dai  Anyuan Gao  Chuan Liu  Jian Liu  Huafeng Yang  Xiaowei Liu  Bin Cheng  Kunji Chen  Zhenlin Wang  Kenji Watanabe  Takashi Taniguchi  Shi-Jun Liang  Feng Miao 《国家科学评论(英文版)》2021,8(2)

Compared to human vision, conventional machine vision composed of an image sensor and processor suffers from high latency and large power consumption due to physically separated image sensing and processing. A neuromorphic vision system with brain-inspired visual perception provides a promising solution to the problem. Here we propose and demonstrate a prototype neuromorphic vision system by networking a retinomorphic sensor with a memristive crossbar. We fabricate the retinomorphic sensor by using WSe₂/h-BN/Al₂O₃ van der Waals heterostructures with gate-tunable photoresponses, to closely mimic the human retinal capabilities in simultaneously sensing and processing images. We then network the sensor with a large-scale Pt/Ta/HfO₂/Ta one-transistor-one-resistor (1T1R) memristive crossbar, which plays a similar role to the visual cortex in the human brain. The realized neuromorphic vision system allows for fast letter recognition and object tracking, indicating the capabilities of image sensing, processing and recognition in the full analog regime. Our work suggests that such a neuromorphic vision system may open up unprecedented opportunities in future visual perception applications.  相似文献   

Erratum to “The conflict detection and resolution in knowledge merging for image annotation” [Information Processing and Management 42 (2006) 1030–1055]     

Chen-Yu Lee  Von-Wun Soo 《Information processing & management》2008

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A longitudinal analysis of student participation in a digital collaborative storytelling activity     

Liu  Chen-Chung  Yang  Chen-Yu  Chao  Po-Yao 《Educational technology research and development : ETR & D》2019,67(4):907-929

Despite the positive potential of the online social networking platforms, the longitudinal studies regarding how children participate in digital storytelling communities is still scant in the literature. This study investigated how 26 elementary students participated in a 2-year digital storytelling community mediated by a social network application. By analyzing the students’ weekly responses, social networks, and their language learning performance, the results suggested that their oral reading proficiency improved along with their participation in the long-term activity. It was also found that the community features impacted the students’ sense of engagement in the activity. The feature of the learning community that allows students to team up with partners to complete a story improved their engagement and motivation. The social network analysis found that multiple literacies including multimedia processing, language, and collaboration were all considered by students as important criteria for the partnership to complete the collaborative digital storytelling work. However, such a prolonged collaborative digital storytelling activity also introduced new challenges for those students demonstrating unfavorable collaboration profiles as they needed to learn how to collaborate in order to team up with others. The implications of the findings for educational practice are discussed.

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