Sub Network

Sub-networks are smaller, specialized components extracted from larger neural networks, aiming to improve efficiency and adaptability. Current research focuses on automated discovery of optimal sub-networks using evolutionary algorithms and knowledge distillation techniques, often applied to convolutional neural networks (CNNs) and vision transformers. These methods address challenges in continual learning, hardware-constrained inference, and efficient model deployment, leading to faster and more resource-friendly deep learning applications across various domains, including image classification and object detection. The resulting smaller, faster models are particularly impactful for resource-limited devices and real-time applications.