Current fundus image analysis models are predominantly built for specific tasks relying on individual datasets. The learning process is usually based on data-driven paradigm without prior knowledge. To address this issue, we propose MM-Retinal, a ...

Polyp segmentation in colonoscopy images is essential for preventing Colorectal cancer (CRC). Existing polyp segmentation models often struggle with costly pixel-wise annotations. Conversely, datasets can be annotated quickly and affordably using ...

Weakly-supervised medical image segmentation is a challenging task that aims to reduce the annotation cost while keep the segmentation performance. In this paper, we present a novel framework, SimTxtSeg, that leverages simple text cues to generate ...

The effectiveness of knee rehabilitation systems in aiding patients with rehabilitation training has been well-documented. Presently, there is an increasing emphasis on the wearing comfort and user engagement of these systems. In this paper, a ...

Despite extensive algorithms for epilepsy prediction via machine learning, most models are tailored for offline scenarios and cannot handle actual scenarios where data changes over time. Catastrophic forgetting(CF) for learned ...

• Proposed Patient-IL adapts to dynamic patient increase for seizure prediction, facilitating EEG-based incremental learning studies.
• Proposed MP strategy tackles CF in epilepsy prediction due to EEG data interference, integrating ...

Predicting a potential collision with leading vehicles is an essential functionality of any autonomous/assisted driving system. One bottleneck of existing vision-based solutions is that their updating rate is limited to the frame rate of standard ...

Recovering the camera motion and scene geometry from visual data is a fundamental problem in computer vision. Its success in conventional (frame-based) vision is attributed to the maturity of feature extraction, data association and multi-view ...

Implicit scene representation has attracted a lot of attention in recent research of computer vision and graphics. Most prior methods focus on how to reconstruct 3D scene representation from a set of images. In this work, we demonstrate the ...

The design and development of text-based knowledge graph completion (KGC) methods leveraging textual entity descriptions are at the forefront of research. These methods involve advanced optimization techniques such as soft prompts and contrastive ...

Recovering structures from images with 180∘ or 360∘ FoV is pivotal in computer vision and computational photography, particularly for VR/AR/MR and autonomous robotics applications. Due to varying distortions and the complexity of indoor scenes, ...

The minimum feedback arc set problem (FASP), which seeks to remove a minimum set of arcs from a directed graph to make the remaining graph acyclic, is fundamental in graph algorithms with many applications in social network analysis, circuit ...

• New reduction rule for the Feedback Arc Set Problem is studied.
• Efficient reduction algorithms with time guarantees are designed.
• Divide-and-conquer heuristic is proposed to solve large graphs.
• Extensive experiments compare the ...

This monograph introduces various value-based approaches for solving the policy evaluation problem in the online reinforcement learning (RL) scenario, which aims to learn the value function associated with a specific policy under a single Markov ...

With the increasing prominence of deep neural networks in synthetic voice detection, the emergence of adversarial attacks poses a significant threat to the robustness of these detectors. Currently, mainstream methods for generating adversarial ...

Vortical flow animation has attracted considerable attention within the realm of computer graphics. Given that boundaries are the source of vorticity, we introduce a novel approach for the wall-bounded flow simulation in the vortex dynamics ...

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• A boundary treatment method to accurately describe the boundary vorticity generation.
• A computation method for boundary viscosity to capture the boundary layer dynamics.
• A vortex dynamics approach to simulate the complex wall-...

Many program verification tools provide automation via SMT solvers, allowing them to automatically discharge many proofs. However, when a proof fails, it can be hard to understand why it failed or how to fix it. The main feedback the developer ...

Session-based recommendation leverages the short-term interaction sequence to predict the next item a user is most likely to click on. Generally, in real applications, users often click on different types of items in the same session, which makes ...

• LAP-SR is based on personalized diversity to alleviate the long-tail effect.
• The model consists of an initial recommendation model and a post-processing model.
• LAP-SR is a universal post-processing model for session-based ...

Soft wearable robotics presents an opportunity to bridge robotics and textiles, offering lightweight, flexible, and ergonomic solutions for human-robot interaction, but previous studies on wearable soft robotics primarily focus on actuator performance ...

This research concentrates on the elderly user group, proposing an innovative dynamic adaptive visualization mechanism within the realm of in-vehicle human-machine interface (HMI). The essence of this mechanism is the real-time analysis of users’ ...

• First long-term dynamic maps of intensive forage acreage are generated.
• Dynamic monthly composite images (DMCI) improve intensive forage mapping accuracy.
• DMCI- and phenology-based intensive forage mapping approach is robust and ...

The increasing demand for livestock feed in China has led to a remarkable increase in forage acreage, particularly in forage fields under intensive agricultural management. However, there are no maps currently available to demonstrate and ...

Effective user representations are pivotal in personalized advertising. However, stringent constraints on training throughput, serving latency, and memory, often limit the complexity and input feature set of online ads ranking models. This challenge is ...