Tasks ASS:Visualize Activation Maps: Description: Visualize activation maps to understand which image regions activate CNN filters for age detection. Guidelines: You can use any of your pre trained model (made by you) for this task. GUI is not necessary for this task. ASS-2:Age and Emotion Detection through voice: Description: In this task, you will develop a machine learning model to detect a person’s age from a voice note. The model should only process male voices; if a female voice is detected, it should reject the input and display a message saying, “Upload male voice.” If the person’s age is more than 60, the model should mark them as a senior citizen and detect their emotion. For individuals below 60, the model should only detect their age. Guidelines: This task is designed to test your logic-building and problem-solving skills. We encourage you to embrace the challenge and view it as an opportunity to grow. Please create your own machine learning model and ensure it includes a graphical user interface (GUI). While accuracy is important, we will evaluate your work based on the overall performance of your model and the successful functionality of your GUI. ASS-3: Age Detection for Horror Roller Coaster: Description: In this task, you will develop a machine learning model for real-time age detection on a horror roller coaster. The model should detect the age and gender of people. If the age is less than 13 or greater than 60, the model should display a message saying, “Not allowed” and mark them with a red rectangle. Additionally, the model should store all data, including age, gender, and entry time, in an Excel or CSV file. Guidelines: Create your own machine learning model for this task. While a graphical user interface (GUI) is not mandatory, you are welcome to include one if you wish. Although accuracy is important, we will evaluate your work based on the overall performance of your model and the successful functionality of your GUI.