Continual Learning of Conjugated Visual Representations through Higher-Order Motion Flows

Continual Learning of Conjugated Visual Representations through Higher-Order Motion Flows: A Study on the CMOSFET Model Academic Background In the fields of artificial intelligence and computer vision, continual learning from continuous visual data streams has long been a challenge. Traditional machine learning methods typically rely on the assumpt...

Enhancing Aerial Object Detection with Selective Frequency Interaction Network

Selective Frequency Interaction Network for Improved Aerial Object Detection Background and Problem Statement With the advancements in computer vision, aerial object detection has become a critical research focus in remote sensing. This task aims to identify targets such as vehicles or buildings from aerial images captured at varying angles and alt...

DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG

DeepSleepNet: An Automatic Sleep Stage Scoring Model Based on Single-Channel EEG Background Introduction Sleep has a significant impact on human health, and monitoring sleep quality is crucial in medical research and practice. Typically, sleep experts score sleep stages by analyzing various physiological signals such as electroencephalogram (EEG), ...