Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  evaluates face recognition applied to the real-world application of Facebook. Because papers usually present results in terms of accuracy on constrained face datasets, it is difficult to assess how they would work on natural data in a real-world application.  present a method to automatically gather and extract face images from Facebook, resulting in over 60,000 faces datasets,  evaluate a variety of ll-known face recognition algorithms (PCA, LDA, ICA, SVMs) against holistic performance metrics of accuracy, speed, memory usage, and storage size. SVMs perform best with ~65% accuracy, but lor accuracy algorithms such as IPCA are orders of magnitude more efficient in memory consumption and speed, yielding a more feasible system.
['Brian C. Becker', 'Enrique G. Ortiz']
I am writing a research paper on a idea Evaluation of face recognition techniques for application to facebook
[{"from": "human", "value": "I am writing a research paper on a idea Evaluation of face recognition techniques for application to facebook"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  evaluates face recognition applied to the real-world application of Facebook. Because papers usually present results in terms of accuracy on constrained face datasets, it is difficult to assess how they would work on natural data in a real-world application.  present a method to automatically gather and extract face images from Facebook, resulting in over 60,000 faces datasets,  evaluate a variety of ll-known face recognition algorithms (PCA, LDA, ICA, SVMs) against holistic performance metrics of accuracy, speed, memory usage, and storage size. SVMs perform best with ~65% accuracy, but lor accuracy algorithms such as IPCA are orders of magnitude more efficient in memory consumption and speed, yielding a more feasible system."}]