1. Project number and Title
    #9 - Modeling the Neo-Cortex
2. Should this project be considered for the Best Project award? (yes/no)
no
3. Should this project be considered for the top 3 project awards? (yes/no)
no
4. On a scale of 1 to 10, how would you rate the overall organization/clarity
of the project report? (1-10)
9
5. On a scale of 1 to 10, how would you rate the overall project idea? (1-10)
8
6. On a scale of 1 to 10, how would you rate the overall research
contribution of the project idea, methodology and/or results?  (1-10)
8

Then write approximately 2 pages of helpful feedback to the project's
author(s). The following questions should help you organize your
feedback:

* Overall, is the project report clear, concise, and well-organized?
Yes, good introduction, it ties real well into the project approach and what you're trying to accomplish.  Also very cool idea with actually gathering datasets from infants and using that as basis for your research.  That really seems to ground the concepts you're investigating.
Overall it looks like you had a defined data-set, attempted to validate it with your experiment and commented on the resulting results.

* How does the project idea and methodology fit within the framework of Developmental Robotics?
It directly ties into how the learning of infants can help direct the development of a neural network model.  It also evaluated the concept of a couple neural net approaches.  Providing a good amount of detail for the first time reader and digging into examples of how each performs against a dataset.  It definitely was a good start for looking at these concepts.

* Describe what you like BEST about the project?
The discussion of the interaction with the infants and their ability to identify objects.  Followed by the rationalization of why that made sense.  (basically a discussion of how the learning process over time progress to include more complexity

* Describe what you like LEAST about the project?
none.

* Do the methods, results and contributions of the final project correspond to what was presented in the initial project proposal?
Yes, the final project consists of the proposed ideas with some additional investigation.  There was also addition data and discussions added based on recommendations from the proposal feedback.

* Are there any major details left out with regards to the methods, algorithms, or experimental design described in the report?
Further investigation into why some of the results ended up as they did. (Run more data through the experiments and dig into details about possibilities of why that specific data maybe causing the outcomes your seeing.  Maybe the issue is caused by specific details you're using from that data to classify against?)

* Do the experimental results reported in the paper demonstrate success?
Partially.  It looked like the datasets/algorithms used had a few issues with consistent results.

* Do you have any suggestions for improvement and future work?
Apply this same approach to other neural network algorithms, setup a comparison of performance and also document limitation.
Investigate an approach to object identification with more noise (complex background in the image).  Maybe the neural net data ends up the same after the images are processed to identify specific objects, or maybe not.

* How close is the final project report to being publishable as a conference or journal paper  consider the research papers that were part of the course reading)? What would it take to get there?
It's close, but would require some further experimentation on a larger dataset to reach stronger conclusions.