Results 71 to 80 of about 903,030 (265)

Semantic Activity Recognition

open access: yes, 2008
Extracting automatically the semantics from visual data is a real challenge. We describe in this paper how recent work in cognitive vision leads to significative results in activity recognition for visualsurveillance and video monitoring. In particular we present work performed in the domain of video understanding in our PULSAR team at INRIA in Sophia ...
openaire   +2 more sources

Panoramic Human Activity Recognition

open access: yes, 2022
17 ...
Ruize Han   +5 more
openaire   +2 more sources

Leukemia and Exposure to Potential Benzene Sources in Children From the Mexico City Metropolitan Area, 2010–2021: A Geospatial Analysis

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Leukemia is the most common childhood cancer in Mexico, and acute lymphoblastic leukemia (ALL) is the most frequent subtype. Exposure to high concentrations of benzene has been associated with ALL incidence, particularly in urban areas. This study evaluated the relationship between distance to benzene emission sources and the number
Orlando Rivera Zurita   +5 more
wiley   +1 more source

Human activity recognition algorithm based on the spatial feature for WBAN

open access: yes物联网学报, 2019
Traditional image-based activity recognition algorithms have some problems,such as high computational cost,numerous blind spots and easy privacy leakage.To solve the problem above,the CCLA (convolution-convolutional long short-term memory-attention ...
Chi JIN   +3 more
doaj  

Psychosocial Functioning After Pediatric Bone Sarcoma: Generic and Survivor‐Specific Outcomes in Adolescent and Young Adult Patients

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Pediatric bone sarcoma patients and survivors may experience psychosocial challenges related to childhood cancer after their intensive, body‐altering treatment. This cross‐sectional study aimed to evaluate generic and survivor‐specific psychosocial outcomes in a national cohort of pediatric bone sarcoma patients and survivors, and ...
Hinke van der Hoek   +14 more
wiley   +1 more source

An acoustic activity recognition based on deep reinforcement learning

open access: yes上海师范大学学报. 自然科学版, 2020
Most of previous research normally relied on specific data and manual filtering of outliers for better performance.In this paper,a new strategy of activity recognition was proposed which was entirely free from the constraint of user data and guaranteed ...
LIU Ming, HUANG Jifeng, GAO Hai
doaj   +1 more source

An [Imperfect] Case for Dyadic Research in Pediatric Psychosocial Oncology

open access: yes
Pediatric Blood &Cancer, EarlyView.
Stephanie M. Nanos   +2 more
wiley   +1 more source

Ironic Medications: A Narrative‐Based Psycho‐Educational Intervention to Explore Patient–Provider Communication in Adolescents With Haematological Cancer

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Adolescents with haematological malignancies face significant emotional and relational challenges, often accompanied by difficulties in communicating their needs within the healthcare context. To address these issues, a narrative‐based psycho‐educational intervention based on the creation and prescription of Ironic Medications was ...
Marta Stoppa   +7 more
wiley   +1 more source

BMT4me En Español: Multisite Feasibility and Usability Testing of a Spanish‐Language mHealth Adherence Support App for Spanish‐Speaking Caregivers of Children After Hematopoietic Stem Cell Transplantation and Cancer Treatment

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Medication nonadherence during the first 100 days after pediatric hematopoietic stem cell transplantation (HSCT) and during oncology treatment increases risk for complications. BMT4me is a caregiver‐facing mobile health (mHealth) application providing medication reminders, symptom tracking, and note‐taking features to support ...
Micah A. Skeens   +4 more
wiley   +1 more source

Active transfer learning for activity recognition. [PDF]

open access: yes, 2016
We examine activity recognition from accelerometers, which provides at least two major challenges for machine learning. Firstly, the deployment context is likely to differ from the learning context. Secondly, accurate labelling of training data is time-consuming and error-prone. This calls for a combination of active and transfer learning.
Diethe, Tom, Twomey, Niall, Flach, Peter
openaire   +1 more source

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