Search Results for author:
Found 5 papers, 3 papers with code
Object Attribute Matters in Visual Question Answering
In this paper, we propose a novel VQA approach from the perspective of utilizing object attribute, aiming to achieve better object-level visual-language alignment and multimodal scene understanding.
Multimodal Indoor Localization Using Crowdsourced Radio Maps
Indoor Positioning Systems (IPS) traditionally rely on odometry and building infrastructures like WiFi, often supplemented by building floor plans for increased accuracy.
Robust Human Detection under Visual Degradation via Thermal and mmWave Radar Fusion
The majority of human detection methods rely on the sensor using visible lights (e. g., RGB cameras) but such sensors are limited in scenarios with degraded vision conditions.
Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning
The contribution of this paper is threefold: (1) We proposed a molecular-empowered learning scheme for multi-class cell segmentation using partial labels from lay annotators; (2) The proposed method integrated Giga-pixel level molecular-morphology cross-modality registration, molecular-informed annotation, and molecular-oriented segmentation model, so as to achieve significantly superior performance via 3 lay annotators as compared with 2 experienced pathologists; (3) A deep corrective learning (learning with imperfect label) method is proposed to further improve the segmentation performance using partially annotated noisy data.
An End-to-end Pipeline for 3D Slide-wise Multi-stain Renal Pathology Registration
In this paper, we provide a Docker for an end-to-end 3D slide-wise registration pipeline on needle biopsy serial sections in a multi-stain paradigm.
