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Found 14 papers, 2 papers with code
MedRG: Medical Report Grounding with Multi-modal Large Language Model
Medical Report Grounding is pivotal in identifying the most relevant regions in medical images based on a given phrase query, a critical aspect in medical image analysis and radiological diagnosis.
Safe Chance-constrained Model Predictive Control under Gaussian Mixture Model Uncertainty
We present a chance-constrained model predictive control (MPC) framework under Gaussian mixture model (GMM) uncertainty.
Causal Rule Learning: Enhancing the Understanding of Heterogeneous Treatment Effect via Weighted Causal Rules
In the rule discovery phase, we utilize a causal forest to generate a pool of causal rules with corresponding subgroup average treatment effects.
A novel integrated method of detection-grasping for specific object based on the box coordinate matching
Furthermore, a detection-grasping integrated algorithm based on box coordinate matching (DG-BCM) is proposed to obtain the fusion model of object detection and grasp estimation.
SAM-U: Multi-box prompts triggered uncertainty estimation for reliable SAM in medical image
Recently, Segmenting Anything has taken an important step towards general artificial intelligence.
Study on Intelligent Forecasting of Credit Bond Default Risk
This paper proposes an Intelligent Forecasting Framework for Default Risk that provides precise day-by-day default risk prediction.
An Empirical Study of Capital Asset Pricing Model based on Chinese A-share Trading Data
This paper presents an empirical analysis of the capital asset pricing model using trading data for the Chinese A-share market from 2000 to 2019.
Uncertainty-informed Mutual Learning for Joint Medical Image Classification and Segmentation
Our UML has the potential to explore the development of more reliable and explainable medical image analysis models.
A Novel Improved Mask RCNN for Multiple Targets Detection in the Indoor Complex Scenes
However, indoor scenes are usually complex and there are many types of interference factors, leading to great challenges in the multiple targets detection.
RLM-Tracking: Online Multi-Pedestrian Tracking Supported by Relative Location Mapping
The problem of multi-object tracking is a fundamental computer vision research focus, widely used in public safety, transport, autonomous vehicles, robotics, and other regions involving artificial intelligence.
Passive Indoor Localization with WiFi Fingerprints
This paper proposes passive WiFi indoor localization.
PASTO: Strategic Parameter Optimization in Recommendation Systems -- Probabilistic is Better than Deterministic
In this setting with multiple and constrained goals, this paper discovers that a probabilistic strategic parameter regime can achieve better value compared to the standard regime of finding a single deterministic parameter.
IPAPRec: A promising tool for learning high-performance mapless navigation skills with deep reinforcement learning
This paper studies how to improve the generalization performance and learning speed of the navigation agents trained with deep reinforcement learning (DRL).
A CNN-LSTM Quantifier for Single Access Point CSI Indoor Localization
This paper proposes a combined network structure between convolutional neural network (CNN) and long-short term memory (LSTM) quantifier for WiFi fingerprinting indoor localization.
