L MobileNet

MobileNet is a family of lightweight convolutional neural networks designed for efficient deep learning on resource-constrained devices like mobile phones and embedded systems. Current research focuses on improving MobileNet's accuracy and speed through architectural innovations such as inverted bottlenecks, attention mechanisms, and knowledge distillation, often incorporating elements from other architectures like Vision Transformers. These advancements are significant for deploying deep learning in applications with limited computational power, impacting fields ranging from medical image analysis and autonomous driving to object detection in resource-scarce environments.