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To restore proper blood flow in blocked coronary arteries via angioplasty procedure, accurate placement of devices such as catheters, balloons, and stents under live fluoroscopy or diagnostic angiography is crucial. Identified balloon markers help ...

Inferring step-wise actions to assemble 3D objects with primitive bricks from images is a challenging task due to complex constraints and the vast number of possible combinations. Recent studies have demonstrated promising results on sequential ...

3D object detection is one of the most important components in any Self-Driving stack, but current state-of-the-art (SOTA) lidar object detectors require costly & slow manual annotation of 3D bounding boxes to perform well. Recently, several ...

Voice disorders like dysphonia can significantly impact a person’s quality of life, so proper diagnostic methods are crucial. Previous approaches have primarily used datasets of a single language without considering language independence. This ...

To address the shortcomings in feature representation and abstraction ability of NFs in the field of unsupervised industrial anomaly detection, as well as the ambiguity in determining the decision boundary between normal and anomaly features, ...

• An Anomaly Fusion Strategy is introduced to enable the normalizing flow to establish a clearer decision boundary.
• A Dual-Layer 2D Normalizing Flow Network is proposed, which reduces the loss of feature information.
• The Exponential ...

Central to the digital transformation of the process industry are Digital Twins (DTs), virtual replicas of physical manufacturing systems that combine sensor data with sophisticated data-based or physics-based models, or a combination thereof, to ...

Numerous fields, such as ecology, biology, and neuroscience, use animal recordings to track and measure animal behaviour. Over time, a significant volume of such data has been produced, but some computer vision techniques cannot explore it due to ...

Video Moment Retrieval is a task locating a moment from an untrimmed video that are relevant to a given query. It is a highly challenging multi-modal task due to biased annotations and complex cross-model interaction. In this paper, we propose ...

Representation learning for bipartite graphs is a challenging problem due to its unique structure and characteristics. The primary challenge is the lack of extensive supervised data and the bipartite graph structure, where two distinct types of ...

To improve the recommendation accuracy and offer explanations for recommendations, Reinforcement Learning (RL) has been applied to path reasoning over knowledge graphs. However, in recommendation tasks, most existing RL methods learn ...

• A reinforcement learning network was designed to learn user preferences.
• A path ...

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• Estimating the age of the patient from implicit age clues in health forum posts is important to many emerging health studies.

Broader patient-reported experiences in oncology are largely unknown due to the lack of available information from traditional data sources. Online health community data provide an exploratory way to uncover these experiences at a ...