7 accepted papers
With the accelerated development of Industry 4.0, intelligent manufacturing systems increasingly require efficient task allocation and scheduling in multi-robot systems. However, existing methods rely on domain expertise and face challenges in adapting to dynamic production constraints. Additionally
Zero-shot anomaly detection (ZSAD) aims to identify anomalies in new classes of images, and it’s vital in industry and other fields. Most current methods are based on the multimodal models CLIP and SAM, which have prior knowledge to assist model training, but they are highly dependent on the input o…
As deepfake and adversarial attacks evolve, facial recognition systems are encountering increasingly diverse threats. Most existing face liveness detection algorithms focus on single tasks, like spoofing or deepfake attack detection. The corresponding datasets have limited coverage of attack methods…
Since the advent of flying machines, engineers have strived to develop aircraft that can fly as flexibly as birds. From the original traditional control surface to the controllable morphing wing design, they all aim to improve the flight performance of drones, including the load capacity, maneuverab
Federated learning (FL) allows multiple clients to collectively train a high-performance global model without sharing their private data. However, the key challenge in federated learning is that the clients have significant statistical heterogeneity among their local data distributions, which would…
Multi-Stud Tensioning Machine (MSTM) is a specialized equipment used to open/seal the cover of the Reactor Pressure Vessel (RPV) during nuclear power plant maintenance. The tensioning residual values of the 58 studs are monitored for procedure evaluation. It is time-consuming for human operators to
We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech–two vastly different languages. Because it replaces entire pipelines of hand-engineered components with neural networks, end-to-end learning allows us to handle a diverse variety of s…