Results 111 to 120 of about 792,416 (284)

Reveal flocking of birds flying in fog by machine learning

, 2020
We study the first-order flocking transition of birds flying in low-visibility conditions by employing three different representative types of neural network (NN) based machine learning architectures that are trained via either an unsupervised learning ...
Ai, Bao-quan, Guo, Wei-chen, He, Liang
core  

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

FR3 Path Loss in Outdoor Corridors: Physics-Guided Two-Ray Residual Learning

Mathematics
Accurate path-loss characterization in the upper mid-band is critical for 5G/6G outdoor planning, yet classical deterministic expressions lose fidelity at 18 GHz, and purely data-driven regressors offer limited physical insight.
Jorge Celades-Martínez, Jorge Rojas-Vivanco, Melissa Diago-Mosquera, Alvaro Peña, Jose García   +4 more
doaj   +1 more source

Accelerating Residual Reinforcement Learning With Uncertainty Estimation

IEEE Robotics and Automation Letters
Residual Reinforcement Learning (RL) is a popular approach for adapting pretrained policies by learning a lightweight residual policy that provides corrective actions. While Residual RL is more sample-efficient than finetuning the entire base policy, existing methods struggle with sparse rewards and are designed for deterministic base policies.
Dodeja, Lakshita, Schmeckpeper, Karl, Vats, Shivam, Weng, Thomas, Jia, Mingxi, Konidaris, George, Tellex, Stefanie   +6 more
openaire   +2 more sources

Learning Binary Residual Representations for Domain-specific Video Streaming

, 2017
We study domain-specific video streaming. Specifically, we target a streaming setting where the videos to be streamed from a server to a client are all in the same domain and they have to be compressed to a small size for low-latency transmission ...
Kautz, Jan, Liu, Ming-Yu, Sun, Deqing, Tsai, Yi-Hsuan, Yang, Ming-Hsuan   +4 more
core   +1 more source

Hospital Readmission After Traumatic Brain Injury Hospitalization in Community‐Dwelling Older Adults

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the risk of hospital readmission after an index hospitalization for TBI in older adults. Methods Using data from the Atherosclerosis Risk in Communities (ARIC) study, we used propensity score matching of individuals with an index TBI‐related hospitalization to individuals with (1) non‐TBI hospitalizations (primary analysis)
Rachel Thomas, Connor A. Law, Joan A. Casey, Thomas Mosley, Rebecca F. Gottesman, Ramon Diaz‐Arrastia, Holly Elser, Andrea L. C. Schneider   +7 more
wiley   +1 more source

Lessons Learned From a Delayed‐Start Trial of Modafinil for Freezing of Gait in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Freezing of gait (FOG) in people with Parkinson's disease (PwPD) is debilitating and has limited treatments. Modafinil modulates beta/gamma band activity in the pedunculopontine nucleus (PPN), like PPN deep brain stimulation. We therefore tested the hypothesis that Modafinil would improve FOG in PwPD.
Tuhin Virmani, Lakshmi Pillai, Reid D. Landes, Aliyah Glover, Shannon Doerhoff, Jennifer Kleiner, Mitesh Lotia, Rohit Dhall, Edgar Garcia‐Rill   +8 more
wiley   +1 more source

Terahertz image denoising via multiscale hybrid‐convolution residual network

CAAI Transactions on Intelligence Technology
Terahertz imaging technology has great potential applications in areas, such as remote sensing, navigation, security checks, and so on. However, terahertz images usually have the problems of heavy noises and low resolution.
Heng Wu, Zijie Guo, Chunhua He, Shaojuan Luo, Bofang Song   +4 more
doaj   +1 more source

Cascade residuals guided nonlinear dictionary learning

Computer Vision and Image Understanding, 2018
Abstract In this paper, we aim to extend dictionary learning onto hierarchical image representations in a principled way. To achieve dictionary atoms capture additional information from extended receptive fields and attain improved descriptive capacity, we present a two-pass multi-resolution cascade framework for dictionary learning and sparse coding.
Zhang, Tong, Porikli, Fatih
openaire   +2 more sources

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source