Abstract: This paper proposes a multi-label text classification algorithm based on causal relationships to address the current challenge of accurately capturing label correlations in multi-label text ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...

Field-Programmable Gate Arrays (FPGAs) offer a flexible hardware substrate for accelerating image edge detection, combining high parallelism with reconfigurability to meet real-time throughput and low ...

Multi-label learning addresses classification tasks in which each instance may be associated with multiple, non-exclusive labels. Unlike traditional single-label approaches, multi-label methods must ...

Abstract: Deep convolutional neural networks (CNNs) have been widely used for fundus image classification and have achieved very impressive performance. However, the explainability of CNNs is poor ...