Criminal Data Searching APP (2nd Year) 2018 - 2019
SKILLS INVOLVED: JAVA Swing using NetBeans, MySQL DB &
OBJECTIVE: It’s a JAVA based desktop App to search any
criminal record from database using any
key like IMAGE, USERNAME, or other detail.
DETAIL: Using Image Comparing method using JavaCV we
can compare image of any people to
find in database and if found extract its information.
Portfolio (1st Year) 2017 - Till Now
SKILLS INVOLVED: HTML/CSS/JS
OBJECTIVE: Create a Personal Resume Website
DETAIL: Contain ALl Personal Information including academic details, Projects Details, and Resume
School Management System (2nd Year) 2018 - 2019
SKILLS INVOLVED:JAVAFX using NetBeans & MySQL.
OBJECTIVE: It’s a JAVA based desktop App to manage school-based records.
DETAIL: Create three portals – 1. Admin Portal 2. Teacher Portal 3. Student Portal.
1. Admin Portal used to manage “Teacher & Student portals” login related issues.
2. Teacher Portal includes uploading attendances of respective subjects, etc.
3. Student Portal includes monitoring of their attendances & respective year’s notice, etc.
OBJECTIVE: Implement Btree Searching algorithm in File system Searching. And Differntiate which is better in performance.
DETAIL: Create four Tabs – 1. Home Tab 2. Data Tab 3. Indices 4. Query.
A. Home Tab • Tab in which we are describing our project for what purpose this can be implemented.
B. Data Tab • To create our test Data. • In which we are generating our random data to use it as raw data in project. • The output data is of combination of serial no, Name, Username, Password.
C. Indices • Tab in which we will Index Our Data According to Name, UserName, Password respectively as per our requirement.
D. Query • In this tab we will test our project as per requirement • We calculate search time in Database searching i. Before Indexing ii. After Indexing
OBJECTIVE: Build Real time chat application which, with this application students could be able to avail online doubt support.
DETAIL: Create three Module – 1. Online Chat 2. White Board 3. Code Screen.
1. Online chat: Students can ask doubts from TA through chat.
2. Whiteboard: With the help of white board teachers could explain algorithms and diagrams.
3. Code Screen: Students can share their codes to TA and TA can take control of students screen, and modify it.
CHAT BOX (3rd Year) 2019 - 2020
SKILLS INVOLVED:Java, Android Studio, Firebase.
OBJECTIVE: Build Whatsapp Like App which support individual chatting option and group invitation And it also support Friend Request Option With Login Using Email Id and Password.
DETAIL: Create four Tabs – 1. Chats 2. Groups 3. Contacts 4. Requests.
1. Chats: Chat individually to someone who is already in Friend List.
2. Groups: Chat in Group to which you joined.
3. Contacts: Your Contact List Or Your Friend List.
4. Requests: Send Request To Someone who has joined Chatbox.
Snake Xenzia (3rd Year) 2019 - 2020
SKILLS INVOLVED:Python, Deep Learning, Data Structures Algorithms.
OBJECTIVE: Build an Auto Playable Old Snake Xenzia Game using various Algorithms, Such as BFS, DFS, Deep Neural Networks ANd Others
DETAIL: We have use Open ai pygame which is modified to some extend so that we can implement various algorithms
1. Human: It is Non Autonomous Playing Method Which is only playable by human.
2. BFS/DFS: In this we implement Shortest Path Breadth First Search and Sortest Path Depth First Search.
3. Hamiltonian : Implement Hamiltonian ALgorithm.
4. Monto Carlo : It is Probability Based Algorithm.
5. Deep Neural Network : We Implemented both Training and Testing Phase with reward associated to each steps.
Super Angry Flappy Bird (3rd Year) 2019 - 2020
SKILLS INVOLVED:Python, Deep Learning, Neural Network, Pygame,Tkinter
OBJECTIVE: Build an AI Playable Flappy Bird Game Using Deep Learning
DETAIL: We have use pygame module to build flappy bird game and NEAT to train the neural Network, which also included three different graphics mode
1. Three Different Modes are:
a.) Native Flappy Bird
b.) Super Mario
c.) Angry Bird
2. We use NEAT method to train our flappy.
3. Use Deep Neural Network to train module.