InceptionV3 Model

InceptionV3 is a convolutional neural network (CNN) architecture primarily used for image feature extraction and classification, finding applications in diverse fields like image generation evaluation, medical image analysis, and agricultural applications. Current research focuses on improving InceptionV3's performance and efficiency through techniques such as quantization, transfer learning, and integration with other architectures like SENet and transformers, often addressing challenges related to data imbalance and computational cost. Its widespread use in various image-related tasks highlights its significance as a robust and adaptable tool for computer vision, contributing to advancements in both research and practical applications.