8 papers
SaaF: Scene-Specific Ambiguity-Aware 3D Language Fields towards Interactive Real-World Object Retrieval
Yuga Yano, Daiju Kanaoka, Hakaru Tamukoh +1
We propose Scene-specific Ambiguity-aware 3D Language Fields (SaaF), a novel Gaussian Splatting-based 3D language field designed for interactive object retrieval in a given real-wo…
Hibikino-Musashi@Home 2025 Team Description Paper
Ryohei Kobayashi, Kosei Isomoto, Kosei Yamao +19
This paper provides an overview of the techniques employed by Hibikino-Musashi@Home, which intends to participate in the domestic standard platform league. The team developed a dat…
Techniques for Enhancing Memory Capacity of Reservoir Computing
Atsuki Yokota, Ichiro Kawashima, Yohei Saito +3
Reservoir Computing (RC) is a bio-inspired machine learning framework, and various models have been proposed. RC is a well-suited model for time series data processing, but there i…
Unified Understanding of Environment, Task, and Human for Human-Robot Interaction in Real-World Environments
Yuga Yano, Akinobu Mizutani, Yukiya Fukuda +3
To facilitate human--robot interaction (HRI) tasks in real-world scenarios, service robots must adapt to dynamic environments and understand the required tasks while effectively co…
Enhancing Neural Network Robustness Against Fault Injection Through Non-linear Weight Transformations
Ninnart Fuengfusin, Hakaru Tamukoh
Deploying deep neural networks (DNNs) in real-world environments poses challenges due to faults that can manifest in physical hardware from radiation, aging, and temperature fluctu…
Harden Deep Neural Networks Against Fault Injections Through Weight Scaling
Ninnart Fuengfusin, Hakaru Tamukoh
Deep neural networks (DNNs) have enabled smart applications on hardware devices. However, these hardware devices are vulnerable to unintended faults caused by aging, temperature va…