Inception-v3-Based Recommender System for Crops

Inception-v3 model is an image classifier that is commonly used in predictive modelling using an image as an input. Specifically, it achieved the following objectives a) Identify the major crops grown in the Philippines; b) Identify the soil requirements of crops; c) Classify Soil Texture images using Inception-v3; and d) Develop precision crop framing procedure based on Inception-v3. A threshold was set to 60%. The label having highest score that passes the preset threshold was used as a basis in the recommender system. The Inception-v3 model recognizes very well the images are that are clear and recognizable. Inception-v3 is an excellent tool in developing an image-based recommender system. However, the big challenge for authors who are also planning to do similar system lies on how to train the inception-v3 moel without over or under fitting. What can be done to solve thi issue is to play or manipulate the learning rate and the number of epochs. These are said to be the deterministic parameters to fine tune the model.