video1.0<iframe src="https://www.loom.com/embed/e58a843073014228b3f54890796d5347" frameborder="0" width="1766" height="1324" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>13241766Loomhttps://www.loom.com13241766https://cdn.loom.com/sessions/thumbnails/e58a843073014228b3f54890796d5347-7e1e0c8cbf16e787.gif358.419In this video, I demonstrate my flower image recognition model based on CNN and transfer learning using EfficientNet B0. The model predicts 13 flower species with an impressive accuracy of 94.32% and an F1 score of 0.9434. I showcase live predictions and file selections, achieving high confidence levels, such as 99.6% for marigold. Additionally, I discuss the model's ability to store scan history and visualize accuracy. I encourage viewers to explore the predictions and provide feedback.