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Found 11 papers, 5 papers with code
Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging
Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment.
Hierarchical discriminative learning improves visual representations of biomedical microscopy
Importantly, sampled patches from WSIs of a patient's tumor are a diverse set of image examples that capture the same underlying cancer diagnosis.
MixFormer: End-to-End Tracking with Iterative Mixed Attention
Our core design is to utilize the flexibility of attention operations, and propose a Mixed Attention Module (MAM) for simultaneous feature extraction and target information integration.
Ranked #1 on
Visual Object Tracking
on LaSOT
OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology
Here, we present OpenSRH, the first public dataset of clinical SRH images from 300+ brain tumors patients and 1300+ unique whole slide optical images.
3D Shuffle-Mixer: An Efficient Context-Aware Vision Learner of Transformer-MLP Paradigm for Dense Prediction in Medical Volume
Therefore, designing an elegant and efficient vision transformer learner for dense prediction in medical volume is promising and challenging.
MixFormer: End-to-End Tracking with Iterative Mixed Attention
Our core design is to utilize the flexibility of attention operations, and propose a Mixed Attention Module (MAM) for simultaneous feature extraction and target information integration.
Ranked #4 on
Visual Object Tracking
on GOT-10k
Semi-Supervised Video Object Segmentation
Visual Object Tracking
Two-stream Convolutional Networks for Multi-frame Face Anti-spoofing
Face anti-spoofing is an important task to protect the security of face recognition.
Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence
Conclusion: SRH with trained artificial intelligence models can provide rapid and accurate intraoperative analysis of skull base tumor specimens to inform surgical decision-making.
Target Transformed Regression for Accurate Tracking
Accurate tracking is still a challenging task due to appearance variations, pose and view changes, and geometric deformations of target in videos.
Ranked #1 on
Visual Object Tracking
on VOT2019
Blind deblurring for microscopic pathology images using deep learning networks
Artificial Intelligence (AI)-powered pathology is a revolutionary step in the world of digital pathology and shows great promise to increase both diagnosis accuracy and efficiency.
Fully Convolutional Online Tracking
To tackle this issue, we present the fully convolutional online tracking framework, coined as FCOT, and focus on enabling online learning for both classification and regression branches by using a target filter based tracking paradigm.
