Analyzing the Power of Representation Learning Networks in Deep Models”

The goal of this study is to thoroughly examine the influence and efficacy of representation learning networks in deep models. Examining various network topologies, training strategies, and applications will be the main focus in order to comprehend how these elements contribute to improving feature extraction and overall model performance.i donot want plaigarism and artificial intilegence to finish this paper

CAP 6619: Deep Learning (2023 Fall)
Course Report Instruction
(For students participating in final exam) (10 points)
Due date [December 10 2023, Firm]
This instruction only applies to students who will participate in the final exam (i.e., do NOT
wish to substitute the final exam using term project). If you wish to substitute the final exam
using a longer version of the term project report (i.e., a research report), please follow
“Research Report Instruction” (for students substituting final exam) in the Canvas.
The grading of the term project report is based on the following criteria.
1. Overall [2 pts]: You MUST organize your report in IEEE format, with 1000 words minimum. Please
note that table/figure do not count towards the word limitation. You can use IEEE word or Latex
temperate from the following URL
a. Template: http://www.ieee.org/conferences_events/conferences/publishing/templates.html.
b. Plagiarism: You cannot copy any sentences, paragraphs, or figures, from any external
sources (such as published papers or Internet). If Turnitin indicates that a submission is over
30% similar to any other submissions, the report will receive a penalty score calculated using
formula listed in the term project announcement.
c. If you have to cite a figure/graph published somewhere else, please properly cite the source of
the reference [0 credit if plagiarism check returns over 50% similarity to any published work].
[Grading of grammars and typos are included in the “Overall”]
2. Introduction [1 pt]: Your report should have an introduction section with about 200 words. The
introduction should clearly state (1) what is the research problem to be studied in the report; (2) the
motivation of the problem studied in your report; (3) how are the problem solved by existing
methods, if any; and (4) a brief description about the method you will propose in the report. Cite at
least 5 references related to the project in the Introduction [200 words]
3. Main body [3 pts]: In the body of your project, you will need to provide technical details of your
design [500 words]
a. If your report is about new design to solve a research problem, you will need to describe
motivation of your designs, and detailed framework. Use flowcharts, figures, or some pseudocode to describe your algorithm details. [Use at least one figure (or flowchart) to demonstrate
the system framework or architecture]
b. If you report is using standardized term project (CNN for image classification), this section
should report aspects related to convolutional filters, the architecture of your CNN networks,
any changes or new designs in your framework. [Use at least one figure (or flowchart) to
demonstrate the system framework or architecture]
c. If your report is about experimental studies, you will need to provide a brief description about
your learning/classification methods, the benchmark datasets, and different measures applied.
You should also explain how the experiments are carried out in your study, and what type of
empirical study goals you intend to achieve.
4. Experiments [2 pts]: In the experiments, you need to introduce (1) main purpose of the experimental
studies; (2) what are the tools used to design the algorithms; (3) what are the baseline methods for
comparisons; and (4) what are the performance measures and data used for empirical studies. You
should also use figures and tables to report the results collected from your studies, and summarize the
experimental results [200 words].
a. Experimental settings: including programming tools/languages, the setting of the parameters
used for different methods. [1 pt]
b. The results: The detailed results reported in figures/tables with necessary analysis and
descriptions. You will need to include at least one figure and one table to show the results. [1
pts]
5. Conclusions [1 pt]: In the conclusions, you should briefly summarize the research problem studied in
your report. Explain what you have done and summarize the major findings. Draw any informative
conclusions, which can be useful to guide the followers [100 words, 1 point]
6. References [1 pt]: Please cite at least 5 relevant references in your report. At least 3 of them must be
from 2017 or after.