Results 81 to 90 of about 115,093 (312)

Contrastive Self-Supervised Learning for Sensor-Based Human Activity Recognition: A Review

IEEE Access
Deep learning models have achieved significant success in human activity recognition, particularly in assisted living and telemonitoring. However, training these models requires substantial amounts of labeled training data, which is time-consuming and ...
Hui Chen, Charles Gouin-Vallerand, Kevin Bouchard, Sebastien Gaboury, Melanie Couture, Nathalie Bier, Sylvain Giroux   +6 more
doaj   +1 more source

VoxCeleb2: Deep Speaker Recognition

, 2018
The objective of this paper is speaker recognition under noisy and unconstrained conditions. We make two key contributions. First, we introduce a very large-scale audio-visual speaker recognition dataset collected from open-source media.
Chung, Joon Son, Nagrani, Arsha, Zisserman, Andrew   +2 more
core   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

Raising students' awareness of cross-cultural contrastive rhetoric in English writing via an e-learning course [PDF]

, 2008
This study investigated the potential impact of e-learning on raising overseas students' cultural awareness and explored the possibility of creating an interactive learning environment for them to improve their English academic writing.
Spencer, Ken, Wang, Jinghui, Xing, Minjie   +2 more
core  

Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning

Despite its empirical success, the theoretical foundations of self-supervised contrastive learning (CL) are not yet fully established. In this work, we address this gap by showing that standard CL objectives implicitly approximate a supervised variant we call the negatives-only supervised contrastive loss (NSCL), which excludes same-class contrasts. We
Luthra, Achleshwar, Yang, Tianbao, Galanti, Tomer   +2 more
openaire   +2 more sources

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

Course Recommendation Model Based on Layer Dropout Graph Differential Contrastive Learning

IEEE Access
At present, the course recommendation model of graph collaborative filtering mainly uses bipartite graph modeling to obtain user-course cooperative relationship.
Yong Ouyang, Hao Long, Rong Gao, Jinghang Liu   +3 more
doaj   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

Molecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova, Zuzana Kozovska, Ondrej Pos, Kristina Pavlov, Sachin Gulati, Peter Makovicky, Kristina Jakic, Monika Burikova, Eva Sedlackova, Barbora Svitkova, Silvia Tyciakova, Vojtech Bystry, Nicolas Blavet, Boris Tichy, Matej Hrnciar, Jaroslav Budis, Miroslav Tomas, Peter Dubovan, Georgina Kolnikova, Veronika Repaska, Nikoleta Mojzesova, Eva Zomborska, Daniel Pindak, Michal Mego, Tomas Szemes, Miroslava Matuskova   +25 more
wiley   +1 more source

Learning in Markov Random Fields with Contrastive Free Energies [PDF]

, 2005
Learning Markov random field (MRF) models is notoriously hard due to the presence of a global normalization factor. In this paper we present a new framework for learning MRF models based on the contrastive free energy (CF) objective function.
Sutton, Charles, Welling, Max
core   +1 more source