1 citations · 2 across the 8 of their papers we have counts for
9 papers
AdoDAS: A Privacy-Preserving Multimodal Challenge for Adolescent Depression, Anxiety, and Stress Assessment
Zhaojie Luo, Junkun Wang, Tianhua Qi +11
Adolescent depression, anxiety, and stress (D/A/S) call for scalable tools that complement, rather than replace, professional evaluation. Under a privacy-preserving policy, the Ado…
Zero-shot Sound Event Classification Using a Sound Attribute Vector with Global and Local Feature Learning
Yi-Han Lin, Xunquan Chen, Ryoichi Takashima +1
This paper introduces a zero-shot sound event classification (ZS-SEC) method to identify sound events that have never occurred in training data. In our previous work, we proposed a…
Learn to See Faster: Pushing the Limits of High-Speed Camera with Deep Underexposed Image Denoising
Weihao Zhuang, Tristan Hascoet, Ryoichi Takashima +1
The ability to record high-fidelity videos at high acquisition rates is central to the study of fast moving phenomena. The difficulty of imaging fast moving scenes lies in a trade-…
Optical Flow Regularization of Implicit Neural Representations for Video Frame Interpolation
Weihao Zhuang, Tristan Hascoet, Ryoichi Takashima +1
Recent works have shown the ability of Implicit Neural Representations (INR) to carry meaningful representations of signal derivatives. In this work, we leverage this property to p…
Current Source Localization Using Deep Prior with Depth Weighting
Rio Yamana, Hajime Yano, Ryoichi Takashima +2
This paper proposes a novel neuronal current source localization method based on Deep Prior that represents a more complicated prior distribution of current source using convolutio…
FasterRCNN Monitoring of Road Damages: Competition and Deployment
Hascoet Tristan, Yihao Zhang, Persch Andreas +3
Maintaining aging infrastructure is a challenge currently faced by local and national administrators all around the world. An important prerequisite for efficient infrastructure ma…
Reversible designs for extreme memory cost reduction of CNN training
Tristan Hascoet, Quentin Febvre, Yasuo Ariki +1
Training Convolutional Neural Networks (CNN) is a resource intensive task that requires specialized hardware for efficient computation. One of the most limiting bottleneck of CNN t…
Assisting human experts in the interpretation of their visual process: A case study on assessing copper surface adhesive potency
Tristan Hascoet, Xuejiao Deng, Kiyoto Tai +6
Deep Neural Networks are often though to lack interpretability due to the distributed nature of their internal representations. In contrast, humans can generally justify, in natura…
On zero-shot recognition of generic objects
Tristan Hascoet, Yasuo Ariki, Tetsuya Takiguchi
Many recent advances in computer vision are the result of a healthy competition among researchers on high quality, task-specific, benchmarks. After a decade of active research, zer…