Detection Algorithm

Detection algorithms aim to identify specific patterns or anomalies within data, ranging from images and videos to network traffic and biological signals. Current research emphasizes the use of deep learning, particularly convolutional neural networks (CNNs) like YOLO variants and transformer architectures, for improved accuracy and efficiency, often coupled with techniques like federated learning to address data privacy and scalability concerns. These advancements have significant implications across diverse fields, enabling applications such as autonomous driving, medical diagnosis, cybersecurity, and environmental monitoring.