arXiv:2303.02158
공식 코드 · Papers with Code
BioImageLoader: Easy Handling of Bioimage Datasets for Machine Learning
원문 초록
BioImageLoader (BIL) is a python library that handles bioimage datasets for machine learning applications, easing simple workflows and enabling complex ones. BIL attempts to wrap the numerous and varied bioimages datasets in unified interfaces, to easily concatenate, perform image augmentation, and batch-load them. By acting at a per experimental dataset level, it enables both a high level of customization and a comparison across experiments. Here we present the library and show some application it enables, including retraining published deep learning architectures and evaluating their versatility in a leave-one-dataset-out fashion.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Prompt-Free Conditional Diffusion for Multi-object Image Augmentation
When Large Multimodal Models Confront Evolving Knowledge:Challenges and Pathways
Language-Driven Dual Style Mixing for Single-Domain Generalized Object Detection
Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning
Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.