Noise reduction technology for extracting important features from sensor data filled with noise.
Keywords: Noise removal, denoising, audio processing, image processing, signal processing, feature analysis, signal modeling.
Recently, excellent AI technologies have emerged in areas such as voice recognition, image recognition, and data processing. On the other hand, when these technologies are actually applied in the field, it is often felt that their performance is not as high as expected. This is due to a discrepancy between the data used to train the AI model and the actual data. The causes of this discrepancy arise from differences in sensor characteristics, such as microphones and cameras, as well as differences in sensing environments, meaning variations in types of noise, among other factors. In my research, I am developing data analysis and noise reduction techniques to minimize such discrepancies and maximize the performance of AI models. Additionally, through collaboration with various companies and institutions, I have accumulated know-how regarding sensor placement and environmental setup to minimize the intrusion of noise and unnecessary data. As a "jack of all trades" in signal processing, I solve problems related to various signals, including audio and images, from multiple angles, so please feel free to reach out.
- Company：埼玉大学 オープンイノベーションセンター
- Price：Other
