Results 61 to 70 of about 115,093 (312)

NormFace: L2 Hypersphere Embedding for Face Verification

, 2017
Thanks to the recent developments of Convolutional Neural Networks, the performance of face verification methods has increased rapidly. In a typical face verification method, feature normalization is a critical step for boosting performance.
Cheng, Jian, Wang, Feng, Xiang, Xiang, Yuille, Alan L.   +3 more
core   +1 more source

Cross-modal Contrastive Learning for Multimodal Fake News Detection [PDF]

, 2023
Longzheng Wang, Chuang Zhang, Hongbo Xu, Shuai Zhang, Xiaohan Xu, Siqi Wang   +5 more
openalex   +1 more source

Network Binarization via Contrastive Learning

, 2022
Neural network binarization accelerates deep models by quantizing their weights and activations into 1-bit. However, there is still a huge performance gap between Binary Neural Networks (BNNs) and their full-precision (FP) counterparts. As the quantization error caused by weights binarization has been reduced in earlier works, the activations ...
Shang, Yuzhang, Xu, Dan, Zong, Ziliang, Nie, Liqiang, Yan, Yan   +4 more
openaire   +2 more sources

Improving PARP inhibitor efficacy in bladder cancer without genetic BRCAness by combination with PLX51107

Molecular Oncology, EarlyView.
Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz, Anna L. Bartkowiak, Michael Rose, Nora Kolks, Patrick Petzsch, Vandana Solanki, Anne Stoffel, Bianca Faßbender, Leandra Lepping, Julka Volkamer, Karl Köhrer, Marc Seifert, Tokameh Mahmoudi, Tahlita C. M. Zuiverloon, Günter Niegisch, Michèle J. Hoffmann   +15 more
wiley   +1 more source

PDCNet: A Polarimetric Data-Enhanced Contrastive Learning Network for PolSAR Land Cover Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) has rich polarization information, offering an efficient and reliable means of collecting information. However, how to effectively leverage these complex data to extract polarization features remains a key ...
Bo Ren, Chaoyue Hua, Biao Hou, Jian Lv, Chen Yang, Licheng Jiao, Jocelyn Chanussot   +6 more
doaj   +1 more source

Fine-grained Contrastive Learning for Definition Generation [PDF]

, 2022
Hengyuan Zhang, Dawei Li, Shiping Yang, Yanran Li   +3 more
openalex   +1 more source

Children’s learning from contrast modelling [PDF]

Cognitive Development, 2002
This study investigates the effectiveness of immediately modelling the correct solution to a task on which children were making errors. The technique is based on proposals by Saxton (1997) who, in his contrast theory of negative input, claims that corrective speech input is particularly effective when it immediately follows a child's error, such as an ...
Pine, K. J., Messer, D. J., St. John, K.
openaire   +1 more source

In vitro models of cancer‐associated fibroblast heterogeneity uncover subtype‐specific effects of CRISPR perturbations

Molecular Oncology, EarlyView.
Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra, Shamsudheen Karuthedath Vellarikkal, Lixia Li, Hong Sun, Khoa Nguyen, Amber Montano, Suchitra Natarajan, Federica Piccioni, Alex Michael Tamburino, Xin Yu, Aleksandra Katarzyna Olow   +10 more
wiley   +1 more source

Node classification in complex networks based on multi-view debiased contrastive learning

Complex & Intelligent Systems
In complex networks, contrastive learning has emerged as a crucial technique for acquiring discriminative representations from graph data. Maximizing the similarity among relevant sample pairs while minimizing that among irrelevant pairs is pivotal in ...
Zhe Li, Lei Zhou, Yandong Hou, Min Ji, Zhuanzheng Hang, Bolun Chen   +5 more
doaj   +1 more source

Dual Contrastive Learning Model Based Background Debiasing in SAR ATR

Shuju Caiji Yu Chuli
Contrastive learning， as a self-supervised approach， enables the extraction of target representations from unlabeled SAR images， serving as a critical technique for automatic target recognition （ATR） in SAR.
ZHANG Wenqing, WANG Jing, HUANG Xueqin, TIAN Sirui, HE Cheng, ZHANG Jingdong, LI Hongtao   +6 more
doaj   +1 more source