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๐Ÿ” peter r wild ๐Ÿ“‚ Engineering
Showing 11103 results for "peter r wild" in Engineering
Engineering Preprint PDF DOI

LRS-VoxMM: A benchmark for in-the-wild audio-visual speech recognition

Doyeop Kwak, Jeongsoo Choi, Suyeon Lee, Joon Son Chung ยท 2026

We introduce LRS-VoxMM, an in-the-wild benchmark for audio-visual speech recognition (AVSR). The benchmark is derived from VoxMM, a dataset of diverse real-world spoken conversations with human-annotaโ€ฆ

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Engineering Preprint PDF DOI

Function-based Parametric Co-Design Optimization of Dexterous Hands

Mohammad Amin Mirzaee, Harsh Gupta, Wenzhen Yuan ยท 2026

Despite advances in dexterous hand manipulation, robotic hand design is still largely decoupled from task-driven evaluation and control, limiting systematic optimization. Existing robotic hand co-desiโ€ฆ

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Engineering Preprint PDF DOI

SASI: Leveraging Sub-Action Semantics for Robust Early Action Recognition in Human-Robot Interaction

Yongpeng Cao, Masahiro Hirano, Hyuno Kim, Yuji Yamakawa ยท 2026

Understanding human actions is critical for advancing behavior analysis in human-robot interaction. Particularly in tasks that demand quick and proactive feedback, robots must recognize human actions โ€ฆ

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Engineering Preprint PDF DOI

A Real-time Scale-robust Network for Glottis Segmentation in Nasal Transnasal Intubation

Yang Zhou, Chaoyong Zhang, Ruoyi Hao, Huilin Pan, Yang Zhang, Hongliang Ren ยท 2026

Nasotracheal intubation (NTI) is a critical clinical procedure for establishing and maintaining patient airway patency. Machine-assisted NTI has emerged as a pivotal approach for optimizing proceduralโ€ฆ

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Engineering Preprint PDF DOI

Spectral Dynamic Attention Network for Hyperspectral Image Super-Resolution

Tengya Zhang, Feng Gao, Lin Qi, Junyu Dong, Qian Du ยท 2026

Hyperspectral image super-resolution is essential for enhancing the spatial fidelity of HSI data, yet existing deep learning methods often struggle with substantial spectral redundancy and the limitedโ€ฆ

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Engineering Preprint PDF DOI

PM-EKF: A Physiological Model-Based Extended Kalman Filter for Daily-Life Physical Activity Energy Expenditure Estimation

Shuhao Que, Remco Poelarends, Valentina Breschi, Ying Wang ยท 2026

Monitoring physical activity energy expenditure (PAEE) in daily life is essential for characterizing individual health and metabolic status. Although indirect calorimetry provides gold-standard PAEE mโ€ฆ

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Engineering Preprint PDF DOI

Accelerating Sparse Linear Solvers with an Optical Laser Processing Unit

Dan Gluck, Yotam Mimran, Andrey Karenskih, Talya Vaknin, Omri Wolf, Ruti Ben-Shlomi, Johannes Gebert ยท 2026

Solving large, sparse linear systems is a fundamental workload in scientific computing and engineering simulations, often dominating runtime and energy consumption in high-performance computing (HPC) โ€ฆ

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Engineering Preprint PDF DOI

Sparse Graph Learning from Sparse Data via Fiedler Number Maximization

Bahar Oveisgharan, Gene Cheung, Andrew Eckford ยท 2026

We aim to learn a sparse and connected graph from sparse data, where the number of observations K can be substantially smaller than the signal dimension N for signals x in R^N, and the underlying distโ€ฆ

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Engineering Preprint PDF DOI

FlowS: One-Step Motion Prediction via Local Transport Conditioning

Leandro Di Bella, Adrian Munteanu, Bruno Cornelis ยท 2026

Generative motion prediction must satisfy three simultaneous requirements for real-world autonomy: high accuracy, diverse multimodal futures, and strictly bounded latency. Diffusion models meet the fiโ€ฆ

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Engineering Preprint PDF DOI

Similarity Choice and Negative Scaling in Supervised Contrastive Learning for Deepfake Audio Detection

Jaskirat Sudan, Hashim Ali, Surya Subramani, Hafiz Malik ยท 2026

Supervised contrastive learning (SupCon) is widely used to shape representations, but has seen limited targeted study for audio deepfake detection. Existing work typically combines contrastive terms wโ€ฆ

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Engineering Preprint PDF DOI

GEGLU-Transformer for IMU-to-EMG Estimation with Few-Shot Adaptation

Miroljub Mihailovic, Luca Tonin, Stefano Tortora, Emanuele Menegatti ยท 2026

Reliable estimation of neuromuscular activation is a key enabler for adaptive and personalized control in wearable robotics. However, surface electromyography (EMG) remains difficult to deploy robustlโ€ฆ

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Enabling High Error Tolerance in Satellite Video Transmissions by Generative Semantic Communication

Zixin Zhao, Jingzhi Hu, Geoffrey Ye Li ยท 2026

Low Earth orbit (LEO) satellite relays will significantly extend the coverage of mobile networks, enabling users in remote areas to transmit data of real-time events. Nevertheless, the limited power oโ€ฆ

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Engineering Preprint PDF DOI

EVT-Based Generative AI for Tail-Aware Channel Estimation

Parmida Valiahdi, Niloofar Mehrnia, Walid Saad, Sinem Coleri ยท 2026

Ultra-reliable and low-latency communication (URLLC) will play a key role in fifth-generation (5G) and beyond networks, enabling mission-critical applications. Meeting the stringent URLLC requirementsโ€ฆ

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Engineering Preprint PDF DOI

Wave Tank Experiment for Sea State Monitoring with Distributed Acoustic Sensing

Yoshiyuki Yajima, Sakiko Mishima, Noriyuki Tonami, Tomoyuki Hino, Shugo Aibe, Junichiro Saikawa, Koji Mizuguchi ยท 2026

Monitoring sea states across the offshore wind farm areas is essential to keep their structures safe, efficiently operate the systems, and assess the environmental effects of wind turbines. Conventionโ€ฆ

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Engineering Preprint PDF DOI

Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing

Sakiko Mishima, Yoshiyuki Yajima, Noriyuki Tonami, Tomoyuki Hino, Shugo Aibe, Junichiro Saikawa, Koji Mizuguchi ยท 2026

This study proposes an anomaly-detection framework for monitoring exposure-length variations in submarine free-span cables using Distributed Acoustic Sensing (DAS), which is one of the distributed fibโ€ฆ

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Engineering Preprint PDF DOI

Reachability Analysis of the State Transition and State Covariance Matrices for an LTV System

Fengjiao Liu, Yixiao Zhang, Panagiotis Tsiotras ยท 2026

In this paper, we study the reachability of two closely related matrices appearing in the analysis of linear time-varying (LTV) systems over a finite time interval, namely, its closed-loop state transโ€ฆ

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Semantic Segmentation for Histopathology using Learned Regularization based on Global Proportions

Yangping Li, Thomas Pinetz, Michael Holzel, Marieta Toma, Alexander Effland ยท 2026

In pathology, the spatial distribution and proportions of tissue types are key indicators of disease progression, and are more readily available than fine-grained annotations. However, these assessmenโ€ฆ

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Engineering Preprint PDF DOI

Assessing the dynamic response of long-span bridges under simultaneous wind and traffic loads

Gledson Rodrigo Tondo, Guido Morgenthal ยท 2026

Wind-traffic interactions strongly influence the dynamic response of long-span bridges, yet loads are often analysed independently. This work models concurrent wind and traffic and demonstrates that iโ€ฆ

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$M^2$-VLA: Boosting Vision-Language Models for Generalizable Manipulation via Layer Mixture and Meta-Skills

Siyao Xiao, Yuhong Zhang, Zhifang Liu, Zihan Gao, Jingye Zhang, Sinwai Choo, Dake Zhong, Mengzhe Wang, Xiao Lin, Xianfeng Zhou, Jia Jia, Haoqian Wang ยท 2026

Current Vision-Language-Action (VLA) models predominantly rely on end-to-end fine-tuning. While effective, this paradigm compromises the inherent generalization capabilities of Vision-Language Models โ€ฆ

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Engineering Preprint PDF DOI

EgoLive: A Large-Scale Egocentric Dataset from Real-World Human Tasks

Yihang Li, Xuelong Wei, Jingzhou Luo, Yingjing Xiao, Yibo Bai, Guangyuan Zhou, Teng Zou, Chenguang Gui, Jiajun Wen, He Zhang, Kangliang Chen, Xing Pan, Shuaiyan Liu, Daming Wang, Tao An, Jiayi Li, Shibo Jin, Wanwan Zhang, Tianyu Wang, Boren Wei, Zhixuan Huang, Fangsheng Liu, Ruodai Li, Hui Zhang, Anson Li, Yicheng Gong, Peng Cao, Jiaming Liang, Liang Lin ยท 2026

The advancement of robot learning is currently hindered by the scarcity of large-scale, high-quality datasets. While established data collection methods such as teleoperation and universal manipulatioโ€ฆ

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