Results 41 to 50 of about 2,910,569 (277)

Tangible User Interface and Mu Rhythm Suppression: The Effect of User Interface on the Brain Activity in Its Operator and Observer

open access: yesApplied Sciences, 2017
The intuitiveness of tangible user interface (TUI) is not only for its operator. It is quite possible that this type of user interface (UI) can also have an effect on the experience and learning of observers who are just watching the operator using it ...
Kazuo Isoda   +8 more
doaj   +1 more source

Human Activity Recognition [PDF]

open access: yes, 2005
Motion is an important cue for the human visual system Mobiles have fascinated children, Zeno (circa 500 B.C.) studied moving arrows to pose a paradox and Zeke is investigating the human brain devoted to the understanding of motion. In computer vision research, motion has played an important role for the past thirty years.
Rama Chellappa   +2 more
openaire   +2 more sources

Activity Recognition and Prediction in Real Homes

open access: yes, 2019
In this paper, we present work in progress on activity recognition and prediction in real homes using either binary sensor data or depth video data. We present our field trial and set-up for collecting and storing the data, our methods, and our current ...
A Lotfi   +11 more
core   +1 more source

A Multi-Agent and Attention-Aware Enhanced CNN-BiLSTM Model for Human Activity Recognition for Enhanced Disability Assistance

open access: yesDiagnostics
Background: Artificial intelligence (AI)-based automated human activity recognition (HAR) is essential in enhancing assistive technologies for disabled individuals, focusing on fall detection, tracking rehabilitation progress, and analyzing personalized ...
Mst Alema Khatun   +5 more
doaj   +1 more source

NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

open access: yes, 2019
Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition.
Duan, Ling-Yu   +5 more
core   +1 more source

Pazopanib Combined With Vincristine and Irinotecan in Relapsed Wilms Tumor: Encouraging Outcomes in a Heavily Pretreated Pediatric Cohort

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background While Wilms tumor (WT) typically has a favorable prognosis, relapsed cases—especially those with high‐risk histology—remain therapeutically challenging after intensive frontline therapy. The combination of vincristine and irinotecan has demonstrated activity in pediatric solid tumors, and pazopanib, a multi‐targeted tyrosine kinase ...
Maria Debora De Pasquale   +6 more
wiley   +1 more source

Stratified Transfer Learning for Cross-domain Activity Recognition

open access: yes, 2017
In activity recognition, it is often expensive and time-consuming to acquire sufficient activity labels. To solve this problem, transfer learning leverages the labeled samples from the source domain to annotate the target domain which has few or none ...
Chen, Yiqiang   +4 more
core   +1 more source

Psychosocial Outcomes in Patients With Endocrine Tumor Syndromes: A Systematic Review

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction The combination of disease manifestations, the familial burden, and varying penetrance of endocrine tumor syndromes (ETSs) is unique. This review aimed to portray and summarize available data on psychosocial outcomes in patients with ETSs and explore gaps and opportunities for future research and care.
Daniël Zwerus   +6 more
wiley   +1 more source

On-Device Deep Personalization for Robust Activity Data Collection

open access: yesSensors, 2020
One of the biggest challenges of activity data collection is the need to rely on users and keep them engaged to continually provide labels. Recent breakthroughs in mobile platforms have proven effective in bringing deep neural networks powered ...
Nattaya Mairittha   +2 more
doaj   +1 more source

3D Human Activity Recognition with Reconfigurable Convolutional Neural Networks

open access: yes, 2015
Human activity understanding with 3D/depth sensors has received increasing attention in multimedia processing and interactions. This work targets on developing a novel deep model for automatic activity recognition from RGB-D videos.
Lin, Liang   +4 more
core   +1 more source

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