초청 세미나가 아래와 같이 11월 17일에 진행되오니 관심 있는 분들의 많은 참석 부탁 드립니다.
- 아 래 -
연사: 고정길 교수 (연세대학교 글로벌융합공학부)
제목: Time Series Data Analysis via Deep Learning for Mobile and Embedded Computing Applications
일시: 2021년 11월 17일(수) 오전 11시
장소: 고려대 과학도서관 616B
초록:
This talk will discuss two mobile/embedded systems that involve the analysis of time series data (one numerical and the other image) using deep learning models. The first part of the talk presents HeartQuake, a low cost, accurate, non-intrusive, geophone-based sensing system for extracting accurate electrocardiogram (ECG) patterns using heartbeat vibrations that penetrate through a bed mattress. In HeartQuake, cardiac activity-originated vibration patterns are captured on a geophone and sent to a server, where the data is filtered to remove the sensor’s internal noise and passed on to a bidirectional long short term memory (Bi-LSTM) deep learning model for ECG waveform estimation.
The next half of the talk will present SUGO, a depth video-based system for translating sign language to text using a smartphone's front camera. While exploiting depth-only videos offer benefits such as being less privacy-invasive compared to using RGB videos, it introduces new challenges which include dealing with low video resolutions and the sensors' sensitiveness towards user motion. We overcome these challenges by diversifying our sign language video dataset to be robust to various usage scenarios via data augmentation and design a set of schemes to emphasize human gestures from the input images for effective sign detection. The inference engine of SUGO is based on a 3-dimensional convolutional neural network (3DCNN) to classify a sequence of video frames as a pre-trained word. Furthermore, the overall operations are designed to be light-weight so that that sign language translation takes place in real-time using only the resources available on a smartphone, with no help from cloud servers nor external sensing components.