24 accepted papers
Neural speech synthesis techniques have enabled highly realistic speech deepfakes, posing major security risks. Speech deepfake detection is challenging due to distribution shifts across spoofing methods and variability in speakers, channels, and recording conditions. We explore learning shared disc…
Semi-Supervised Regression (SSR) is essential in domains like sentiment analysis and healthcare where labeled data is limited but unlabeled data is plentiful. Despite its practical importance, SSR remains underexplored due to the lack of effective pseudo-labeling strategies for continuous outputs. U
In order to provide natural and immersive interactive experience for teleoperation in the context of human-robot collaboration and interaction, this work introduces a natural human-robot interaction system for teleoperation based on ultrasonic haptic feedback. Specifically, our system can accurately
Soft sensing is a promising solution to predict key quality variables in various industries. One of the major obstacles to building an accurate data-driven soft sensor is the scarcity of labeled data and the challenge of extracting useful information from unlabeled data. To mitigate this issue, this
Small object detection (SOD) given aerial images suffers from an information imbalance across different feature scales. This makes it extremely challenging to perform accurate SOD. Existing methods, e.g., Feature Pyramid Network (FPN)-based algorithms, focus on extracting high-resolution and low-res
Achieving accurate segmentation in low-light scenes is challenging due to 1) severe domain shift encountered when models trained on daylight data are applied to such scenes and 2) lack of large-scale fine-grained labels in low-light conditions. A good idea is to use the generalization capabilities o
The performance of models trained by Multi-Agent Reinforcement Learning (MARL) is sensitive to perturbations in observations, lowering their trustworthiness in complex environments. Adversarial training is a valuable approach to enhance their performance robustness. However, existing methods often o…
Large-scale outdoor navigation is essential for unmanned ground vehicles (UGVs), but despite significant advancements, they still face two key challenges in practical applications. The first one is how to ensure safe navigation in environments with dynamic and low-lying obstacles that LiDAR cannot d
Topological semantic maps provide a practical solution to enhance indoor navigation for the Partially Sighted or Visually Impaired (PSVI). Segmenting indoor floor plans and extracting boundaries are key to constructing these maps. The existing methods exhibit low accuracy in segmentation. To achieve…
Image captioning is a multi-modal task that enables the transformation from scene images to natural language, providing valuable insights for visually impaired individuals to understand their environment. Therefore, its application to wearable navigation devices for visually impaired individuals hol…
In the fields of robotic perception and computer vision, achieving accurate semantic segmentation of low-light or nighttime scenes is challenging. This is primarily due to the limited visibility of objects and the reduced texture and color contrasts among them. To address the issue of limited visibi…
Although remarkable advances have been achieved in generic object detection, small object detection (SOD) remains challenging owing to small objects’ information loss and noisy representation caused by their non-uniform distribution. Their limited width and height, scale variations, and redundant co…
Petri nets (PNs) are a graphical and mathematical tool to model various event-driven automated systems. Reachability is a fundamental property of PNs. The existence of a non-negative integer solution (NIS) to a state equation is a necessary but not sufficient condition for determining the reachabili
With the advancement of science and technology in recent years, the rate of product upgrading by end users has increased, resulting in a high number of End-Of-Life (EOL) products. For environmental protection and economic benefits, disassembly lines are set up to recycle them. A disassembly line bal
High-dimensional expensive problems are often encountered in the design and optimization of complex robotic and automated systems and distributed computing systems, and they suffer from a time-consuming fitness evaluation process. It is extremely challenging and difficult to produce promising soluti…
Evolutionary algorithms are commonly used to solve many complex optimization problems in such fields as robotics, industrial automation, and complex system design. Yet, their performance is limited when dealing with high-dimensional complex problems because they often require enormous computational…
Real-time and precise prediction for traffic of networks is critically important for allocating the optimal computing/network resources based on users' business requirements, analyzing the network performance, and realizing intelligent congestion control and high-accuracy anomaly detection. The dram…
An environment where a robot swarm attacks a territory protected by another one leads to an attack-defense confrontation problem. Commonly-used deep reinforcement learning-based methods rely on pre-training and become intractable due to the curse of dimensionality. To develop effective attack strate…
High-dimensional and sparse (HiDS) matrices from recommender systems contain various useful patterns. A latent factor (LF) analysis is highly efficient in grasping these patterns. Stochastic gradient descent (SGD) is a widely adopted algorithm to train an LF model. Can its extensions be capable of f
Cloud services have rapidly grown in cloud data centers (CDCs). Accurate workload prediction benefits CDCs since appropriate resource provisioning can be performed for their providers to ensure the full satisfaction of service-level agreement (SLA) requirements from users. Yet these providers face s
Semiconductor manufacturing industry has adopted multi-cluster tools as wafer fabrication equipment that is extraordinarily pricey but highly attractive owing to their higher productivity than single cluster tools can achieve. A challenging issue is how to schedule these tools. It is especially diff…
The best design among many can be selected through their accurate performance evaluation. When such evaluation is based on discrete event simulations, the design selection is extremely time-consuming. Ordinal optimization greatly speeds up this process. Optimal Computing-Budget Allocation (OCBA) has…
Deadlock prevention policies for flexible manufacturing systems (FMS) usually suffer from redundant monitors since some monitors may be added to the siphons that are originally controlled. To eliminate these redundant monitors, the controllability condition of siphons is studied in this work. For a…
Reachability is an important dynamic property of Petri nets. Its determination given an unbounded net and initial marking has remained an open problem since 1960s. Due to its extreme difficulty, a great deal of research has been focused on some subclasses of unbounded nets. For arbitrary ones, this…