Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Studies of ovarian development in female mammals have shown a relationship beten the day in the estrous cycle and the size of the main structures and physiological status of the ovary.  presents an algorithm for the automatic classification of bovine ovaries into temporal categories using information extracted from ultrasound images. The temporal classes corresponded roughly to the metestrus, diestrus, and proestrus phases of the bovine reproductive cycle. Features based on the sizes of ovarian structures formed the patterns on which the classification was performed. A Naive Bayes classifier was able to correctly classify the stage of the estrous cycle for 86.36% of the test patterns. A decision tree classified 100% of the test patterns correctly. The decision tree inference algorithm used to build the classifier constructed a tree that used only two of the five available features indicating that they form a sufficiently rich set of features for robust classification.
['Idalia Maldonado-Castillo', 'Mark G. Eramian', 'Roger Pierson', 'Jaswant Singh', 'Gregg P. Adams']
I am writing a research paper on a idea Classification of Bovine Reproductive Cycle Phase using Ultrasound-Detected Features
[{"from": "human", "value": "I am writing a research paper on a idea Classification of Bovine Reproductive Cycle Phase using Ultrasound-Detected Features"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Studies of ovarian development in female mammals have shown a relationship beten the day in the estrous cycle and the size of the main structures and physiological status of the ovary.  presents an algorithm for the automatic classification of bovine ovaries into temporal categories using information extracted from ultrasound images. The temporal classes corresponded roughly to the metestrus, diestrus, and proestrus phases of the bovine reproductive cycle. Features based on the sizes of ovarian structures formed the patterns on which the classification was performed. A Naive Bayes classifier was able to correctly classify the stage of the estrous cycle for 86.36% of the test patterns. A decision tree classified 100% of the test patterns correctly. The decision tree inference algorithm used to build the classifier constructed a tree that used only two of the five available features indicating that they form a sufficiently rich set of features for robust classification."}]