572+ open-access research outputs.
Gaussian basis functions provide an efficient and flexible alternative to spline activations in KANs. In this work, we introduce the partition-of-unity Gaussian KAN (PU-GKAN), a Shepard-type normalizeโฆ
This study proposes post-quantum encrypted control systems based on dynamic-key Learning with Errors (LWE) encryption schemes. The proposed method develops update maps that simultaneously update the pโฆ
Indoor positioning is an essential technology for a wide range of applications in GNSS-denied environments, including indoor navigation and IoT systems. Combining convolutional neural networks (CNNs) โฆ
This paper introduces PHOTON (PHysical Optical Tracking of Notes), a non-invasive optical sensing system for measuring key-lever motion in historical keyboard instruments. PHOTON tracks the vertical dโฆ
Brain-inspired non-Boolean computing offers intrinsic error tolerance and parallelism, but its practical deployment is limited by the lack of compact, energy-efficient spiking hardware compatible withโฆ
Infrastructure-based localization enhances road safety and traffic management by providing state estimates of road users. Development is hindered by fragmented, application-specific stacks that tightlโฆ
The Gaussian scale parameter \(\epsilon\) is central to the behavior of Gaussian Kolmogorov--Arnold Networks (KANs), yet its role in deep edge-based architectures has not been studied systematically. โฆ
Accurate segmentation of gastrointestinal (GI) organs in magnetic resonance enterography (MRE) is critical for diagnosing inflammatory bowel disease (IBD). However, anatomical variability, class imbalโฆ
Robots are increasingly entering human-interactive scenarios that require understanding of quantity. How intelligent systems acquire abstract numerical concepts from sensorimotor experience remains a โฆ
Secret key generation (SKG) from wireless channel reciprocity has been demonstrated on WiFi, LTE, and LoRaWAN, but has never been demonstrated on 5G New Radio (NR) Sounding Reference Signal (SRS) and โฆ
Spatiotemporal chaos in fluid systems exhibits severe parametric sensitivity, rendering classical adjoint-based optimal control intractable because each operating regime requires recomputing the contrโฆ
We present EgoNav, a system that enables a humanoid robot to traverse diverse, unseen environments by learning entirely from 5 hours of human walking data, with no robot data or finetuning. A diffusioโฆ
Battery health management is heavily dependent on reliable State-of-Health (SoH) estimation to ensure battery safety with maximized energy utilization. Although SoH estimation can effectively track baโฆ
Real-time 30-to-60 fps video frame interpolation on mobile neural processing units (NPUs) requires each synthesized frame within 33.3 ms. We show that mainstream flow-based video frame interpolation fโฆ
Sign language recognition (SLR) is vital for bridging communication gaps between deaf and hearing communities. Vision-based approaches suffer from occlusion, computational costs, and physical constraiโฆ
Reliable estimation of surgical needle 3D position and orientation is essential for autonomous robotic suturing, yet existing methods operate almost exclusively under stereoscopic vision. In monocularโฆ
Given the popularity of 360{\deg} images on social media platforms, 360{\deg} image compression becomes a critical technology for media storage and transmission. Conventional 360{\deg} image compressiโฆ
Training generalist robots demands large-scale, diverse manipulation data, yet real-world collection is prohibitively expensive, and existing simulators are often constrained by fixed asset libraries โฆ
Inertial navigation using low-cost MEMS sensors is plagued by rapid drift due to sensor noise and bias instability. While recent data-driven approaches have made significant strides, they often struggโฆ
Autonomous bicycles offer a promising agile solution for urban mobility and last-mile logistics, however, conventional control strategies often struggle with their underactuated nonlinear dynamics, suโฆ
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