765 citations · 2.1k across the 63 of their papers we have counts for
15 papers · 1 filter
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
Cheng Chen, Juzheng Miao, Dufan Wu +10
The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation ta…
Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classification
Haixing Dai, Lu Zhang, Lin Zhao +9
With the popularity of deep neural networks (DNNs), model interpretability is becoming a critical concern. Many approaches have been developed to tackle the problem through post-ho…
Review of Large Vision Models and Visual Prompt Engineering
Jiaqi Wang, Zhengliang Liu, Lin Zhao +18
Visual prompt engineering is a fundamental technology in the field of visual and image Artificial General Intelligence, serving as a key component for achieving zero-shot capabilit…
SAMAug: Point Prompt Augmentation for Segment Anything Model
Haixing Dai, Chong Ma, Zhiling Yan +14
This paper introduces SAMAug, a novel visual point augmentation method for the Segment Anything Model (SAM) that enhances interactive image segmentation performance. SAMAug generat…
SAM for Poultry Science
Xiao Yang, Haixing Dai, Zihao Wu +7
In recent years, the agricultural industry has witnessed significant advancements in artificial intelligence (AI), particularly with the development of large-scale foundational mod…
Learning Better Contrastive View from Radiologist's Gaze
Sheng Wang, Zixu Zhuang, Xi Ouyang +6
Recent self-supervised contrastive learning methods greatly benefit from the Siamese structure that aims to minimizing distances between positive pairs. These methods usually apply…
Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT
Zhenxiang Xiao, Yuzhong Chen, Lu Zhang +14
Prompts have been proven to play a crucial role in large language models, and in recent years, vision models have also been using prompts to improve scalability for multiple downst…
BI AVAN: Brain inspired Adversarial Visual Attention Network
Heng Huang, Lin Zhao, Xintao Hu +4
Visual attention is a fundamental mechanism in the human brain, and it inspires the design of attention mechanisms in deep neural networks. However, most of the visual attention st…
Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations
Lin Zhao, Haixing Dai, Zihao Wu +8
Artificial neural networks (ANNs), originally inspired by biological neural networks (BNNs), have achieved remarkable successes in many tasks such as visual representation learning…
Rectify ViT Shortcut Learning by Visual Saliency
Chong Ma, Lin Zhao, Yuzhong Chen +7
Shortcut learning is common but harmful to deep learning models, leading to degenerated feature representations and consequently jeopardizing the model's generalizability and inter…
Discovering Dynamic Functional Brain Networks via Spatial and Channel-wise Attention
Yiheng Liu, Enjie Ge, Mengshen He +6
Using deep learning models to recognize functional brain networks (FBNs) in functional magnetic resonance imaging (fMRI) has been attracting increasing interest recently. However,…
Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning
Chong Ma, Lin Zhao, Yuzhong Chen +15
Learning harmful shortcuts such as spurious correlations and biases prevents deep neural networks from learning the meaningful and useful representations, thus jeopardizing the gen…
Mask-guided Vision Transformer (MG-ViT) for Few-Shot Learning
Yuzhong Chen, Zhenxiang Xiao, Lin Zhao +10
Learning with little data is challenging but often inevitable in various application scenarios where the labeled data is limited and costly. Recently, few-shot learning (FSL) gaine…
Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)
Yu Zhao, Xiang Li, Wei Zhang +5
Simultaneous modeling of the spatio-temporal variation patterns of brain functional network from 4D fMRI data has been an important yet challenging problem for the field of cogniti…
Morphological Analusis Of The Left Ventricular Eendocardial Surface Using A Bag-Of-Features Descriptor
Anirban Mukhopadhyay, Zhen Qian, Suchendra M. Bhandarkar +3
The limitations of conventional imaging techniques have hitherto precluded a thorough and formal investigation of the complex morphology of the left ventricular (LV) endocardial su…