Contrastive Mapping Learning for Spatial Reconstruction of Single-Cell RNA Sequencing Data

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Bioengineering,
Single-cell RNA sequencing   Spatial transcriptomics   Contrastive learning   Cell correspondence   Gene expression  

Single-cell RNA sequencing (scRNA-seq) technology enables high-throughput transcriptomic profiling at single-cell resolution, significantly advancing research in cell biology. However, a notable limitation of scRNA-seq is that it requires tissue dissociation, resulting in the loss of the original spatial location information of cells within tissues...

DRTN: Dual Relation Transformer Network with Feature Erasure and Contrastive Learning for Multi-Label Image Classification

Information Science, Computer Science, Artificial Intelligence,
Multi-label image classification   Transformer   Pseudo-region   Feature erasure   Contrastive learning  

New Breakthrough in Multi-Label Image Classification: Dual Relation Transformer Network Academic Background Multi-Label Image Classification (MLIC) is a fundamental yet highly challenging problem in the field of computer vision. Unlike single-label image classification, MLIC aims to assign multiple labels to objects within a single image. Due to th...

Exploiting Instance-Label Dynamics through Reciprocal Anchored Contrastive Learning for Few-Shot Relation Extraction

Information Science, Computer Science, Artificial Intelligence,
Few-shot relation extraction   Contrastive learning   Pre-train   Fine-tune   Information extraction  

Exploiting Instance-Label Dynamics through Reciprocal Anchored Contrastive Learning for Few-Shot Relation Extraction Academic Background In the field of Natural Language Processing (NLP), Relation Extraction (RE) is a fundamental task aimed at identifying and extracting relationships between entities in text. However, traditional supervised learnin...