Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection

no code implementations • 4 Mar 2024 • Jieren Deng, Haojian Zhang, Kun Ding, Jianhua Hu, Xingxuan Zhang, Yunkuan Wang

This paper presents Incremental Vision-Language Object Detection (IVLOD), a novel learning task designed to incrementally adapt pre-trained Vision-Language Object Detection Models (VLODMs) to various specialized domains, while simultaneously preserving their zero-shot generalization capabilities for the generalized domain.

Incremental Learning object-detection +2

VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence

no code implementations • 8 Oct 2023 • Jianing Qiu, Jian Wu, Hao Wei, Peilun Shi, Minqing Zhang, Yunyun Sun, Lin Li, Hanruo Liu, Hongyi Liu, Simeng Hou, Yuyang Zhao, Xuehui Shi, Junfang Xian, Xiaoxia Qu, Sirui Zhu, Lijie Pan, Xiaoniao Chen, Xiaojia Zhang, Shuai Jiang, Kebing Wang, Chenlong Yang, Mingqiang Chen, Sujie Fan, Jianhua Hu, Aiguo Lv, Hui Miao, Li Guo, Shujun Zhang, Cheng Pei, Xiaojuan Fan, Jianqin Lei, Ting Wei, Junguo Duan, Chun Liu, Xiaobo Xia, Siqi Xiong, Junhong Li, Benny Lo, Yih Chung Tham, Tien Yin Wong, Ningli Wang, Wu Yuan

To be commensurate with this capacity, in addition to the real data used for pre-training, we also generated and leveraged synthetic ophthalmic imaging data.

Disease Prediction Representation Learning

Incremental Prototype Tuning for Class Incremental Learning

no code implementations • 7 Apr 2022 • Jieren Deng, Jianhua Hu, Haojian Zhang, Yunkuan Wang

Class incremental learning(CIL) has attracted much attention, but most existing related works focus on fine-tuning the entire representation model, which inevitably results in much catastrophic forgetting.

Class Incremental Learning Incremental Learning

RZiMM-scRNA: A regularized zero-inflated mixture model framework for single-cell RNA-seq data

no code implementations • 25 Oct 2021 • Xinlei Mi, William Bekerman, Peter A. Sims, Peter D. Canoll, Jianhua Hu

Applications of single-cell RNA sequencing in various biomedical research areas have been blooming.

Clustering