71 citations · 97 across the 8 of their papers we have counts for
8 papers
Instance-Wise Adaptive Tuning and Caching for Vision-Language Models
Chunjin Yang, Fanman Meng, Shuai Chen +2
Large-scale vision-language models (LVLMs) pretrained on massive image-text pairs have achieved remarkable success in visual representations. However, existing paradigms to transfe…
Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting
Berend Jelmer Dirk Gort, Xiao-Yang Liu, Xinghang Sun +3
Designing profitable and reliable trading strategies is challenging in the highly volatile cryptocurrency market. Existing works applied deep reinforcement learning methods and opt…
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection
Yongchun Zhu, Dongbo Xi, Bowen Song +4
With the explosive growth of the e-commerce industry, detecting online transaction fraud in real-world applications has become increasingly important to the development of e-commer…
Neural Hierarchical Factorization Machines for User's Event Sequence Analysis
Dongbo Xi, Fuzhen Zhuang, Bowen Song +6
Many prediction tasks of real-world applications need to model multi-order feature interactions in user's event sequence for better detection performance. However, existing popular…
Region-of-interest guided Supervoxel Inpainting for Self-supervision
Subhradeep Kayal, Shuai Chen, Marleen de Bruijne
Self-supervised learning has proven to be invaluable in making best use of all of the available data in biomedical image segmentation. One particularly simple and effective mechani…
A New Local Transformation Module for Few-shot Segmentation
Yuwei Yang, Fanman Meng, Hongliang Li +3
Few-shot segmentation segments object regions of new classes with a few of manual annotations. Its key step is to establish the transformation module between support images (annota…
Class Activation Map generation by Multiple Level Class Grouping and Orthogonal Constraint
Kaixu Huang, Fanman Meng, Hongliang Li +3
Class activation map (CAM) highlights regions of classes based on classification network, which is widely used in weakly supervised tasks. However, it faces the problem that the cl…
Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation
Shuai Chen, Gerda Bortsova, Antonio Garcia-Uceda Juarez +2
We propose a novel semi-supervised image segmentation method that simultaneously optimizes a supervised segmentation and an unsupervised reconstruction objectives. The reconstructi…