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Computing Mechanisms Lab
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A lab that tackles real-world problems with image and signal processing and deep learning.
AboutAbout the lab
Image and data science that transforms real-world problem solving
The Computing Mechanisms Lab conducts research aimed at creating new technologies that combine image and signal processing with deep learning, and at deepening them academically.
Its research covers four application areas: biometrics, medical image processing, 3D computer vision, and data science.
In data science, the lab analyzes signals and data through industry-academia joint research and interdisciplinary collaborative research.
The lab belongs to the Computational Science Division of the Department of Computer and Mathematical Sciences, Graduate School of Information Sciences.
Key terms
- Biometrics
- Authentication technology that verifies a person's identity using physical or behavioral characteristics such as the face or fingerprints
- Deep learning
- A method in which a neural network with many stacked layers learns patterns from large amounts of data
- Image matching
- Processing that finds and links points corresponding to the same location across multiple images
ResearchResearch themes
The lab aims to create new technologies that combine image and signal processing with deep learning, and to deepen them academically. As image and data science that transforms real-world problem solving, it conducts broad research across four application areas.
*Illustrative imagePersonal Authentication Using Biometric Information
Biometrics refers to authentication technologies that use an individual's physical or behavioral characteristics. The lab studies high-performance authentication algorithms and the security of authentication systems for biometric features such as the face, fingerprints, iris, and palmprints.
*Illustrative imageSupporting Differential Diagnosis of Diseases from Medical Images
As an essential technology for computer-aided diagnosis, the lab studies image processing and analysis techniques that support the differential diagnosis of various diseases from medical images captured by MRI, ultrasound, OCT, and other modalities.
*Illustrative imageReconstructing 3D Object Shapes from Images
This technology reconstructs the 3D shape of an object from multiple images. Using image matching techniques that combine image and signal processing with deep learning, the lab studies high-accuracy, high-quality 3D reconstruction methods.
*Illustrative imageA New Framework for Signal and Data Analysis
Through industry-academia joint research and interdisciplinary collaborative research, the lab is working to open up new paradigms for analyzing one-dimensional and multidimensional signals and data, and to put them to practical use.
MembersFaculty
- Professor (Concurrent)Takafumi Aoki
- Associate ProfessorKoichi Ito
- Project Associate ProfessorKeisuke Maeda
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Fingerprint scanner identification” Rachmaninoff / CC BY-SA 3.0 (cropped)
- Personal Authentication Using Biometric Information: “Biometrics ( )” Toshiyuki IMAI / CC BY-SA 2.0 (cropped)
- Supporting Differential Diagnosis of Diseases from Medical Images: “Diagnostic Imaging and Radiology Facility in Navi Mumbai, Maharashtra, India” Goleisureintl / CC BY-SA 4.0 (cropped)
- Reconstructing 3D Object Shapes from Images: “Sugar cane shell in Meshroom - visualization” Colin Kranz / CC BY-SA 4.0 (cropped)
- A New Framework for Signal and Data Analysis: “Typical-workflow” Volkdentoklin / CC BY-SA 4.0 (cropped)
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