5 Project Ideas For Final Year

 

Here’s a List of 5 Project Ideas for Final Year Students:

1. Web Development

• E-Commerce Website: The most demanding project which requires complete knowledge of full-stack development, technologies like MERN and MEAN can be used to build this project. You need to have a good grip on JavaScript. It can have features like NavBar which includes order lists, payment methods, filtering methods, etc. A good UI and a strong back-end are all needed for a perfect e-commerce website. This when added to your resume showcases your skill. 
   
• Smart Security Application: This is a real-world problem that every one of us faces whether working in an organization or being an individual. Using this, you can monitor and manage the security systems anytime, anywhere. You get the authority to control your security in your comfort place. It can include features like detecting the location, having GPS installed in it, and setting an alarm in case of an emergency. One can even secure personal data using APIs which avoids unauthorized access. 
   
• Portfolio Application: This application generates a portfolio describing your work, skills, projects, and everything using a graph in minutes. You just need to fill in entries of your data.  A fully-responsive and solid website can be built using NodeJS and Express, also working with databases, AJAX requests with JQuery, and REST API is implemented. You can apply several concepts in one to see a working and realistic project.

2. Python

• Reminder Application: In this era where every one of us is busy in life, a reminder application would be of great help. This application sends us an alert message in case of any emergency which helps us in solving daily tasks. It includes features like setting a reminder, checking for time-out conditions, and has a calculator in it. Import certain libraries like calculator, notification_alert, and time to make the code short and clear. You can also click on the Birthday Reminder Application in Python to view the source code. 
   
• Language Translator: There are approximately 7100 languages spoken worldwide and when you may need such an application as a language translator, you never know. So, this device translates languages to the language in which you’re comfortable which would help in clear communication among individuals. Import modules like Translate and Tkinter are needed along with basic knowledge of functions. You can also check the Language Translator to know about the work.
   
• Online Grocery Recommender System: This system recommends freshly added groceries for daily purposes. You can order items by just sitting at home. There will be two access points, admin and user. Users are the customers who buy groceries and the admin is the person who handles the data stored in it. It includes features like notification pop-ups, order history, profile settings, etc. 

3. Java

• Course Management System: This system has updated course content and includes features like free and paid content, a search bar, and filter content based on the new and old ones. This can be implemented using the tools for asynchronous bulletin board messaging or real-time chat included in the Course Management System. It includes three modules – administrator, student, and instructor module for smooth functioning of the system. 
   
• Employee Tracking System: This application will keep track of employees’ performance and will also check attendance for regularization. It would be of great help to the organizations to maintain the data of employees. It is developed in Java GUI technology and SQLite is used for the database. You can also refer to our Employee Management System to gain more insight.
   
• E-Healthcare System: Covid era was so scary and to tackle with lots of hustle, developers came up with the idea of healthcare systems that maintain data of patients. This helps in the quick retrieving of data for the management of patients and doctors. You can easily sign up, log in and view one’s profile. Utilization of CRISP-DM (Standard Cross-Industry Process for Data Mining) for the development of an accurate and effective management system is needed for this system. You can also refer to Healthcare Management System to gain more insights. 

 
4. Machine Learning

• Face Detector: This system detects your face by analyzing the structure of the face and matching it with the pre-existing data. It uses machine learning algorithms and analyzes the input and confirms whether the system has the same in the existing database or not. It follows the procedure of capturing the image and relaying it to the back-end with an HTTP form-data request. The data is then saved by the API and matched with the existing database. This can be used in organizations and places where high security is needed. 
   
• Voice Recognition: This system analyzes the tone, and pattern one uses while speaking and on its basis recognizes the voice. It uses Neural Machine Translation to perform machine translation. It can include features like speech recognition and classification, taking voice as input and delivering the output as “Matched Voice”. This can be used in private or public organizations for the entry and exit of working professionals. 
   
• Personality Prediction System: It uses Naive Bayes and Support Vector Machines to operate and predicts the personality based on previous data it contains. It uses “Logistic Regression” to predict the test dataset and determine the personality of an individual.  You can also refer to Personality Prediction System for more insights. It predicts the input based on past classifications. It can include features like testing the input, predicting the output, and optimizing the result. 

5. IoT & CyberSecurity

• IoT-Based Vehicle Accident Detector: This IoT-based detection system detects if there is an obstacle in front of the vehicle using sensors. In case any, it sets an alarm to the driver to change the path or stop the vehicle to avoid an accident. It uses an accelerometer and a GPS sensor. It uses different machine learning models. The Internet of Things (IoT) is used to produce the output when a signal is sent to the cloud by using an accelerometer and a GPS sensor. 
   
• Biometric Attendance System: It uses a fingerprint impression of the user and verifies it with the pre-existing data. It is now widely used in different organizations to track the attendance of employees. It uses Deep Learning Algorithm and has a fingerprint sensor that takes the print as input and matches it, in case if not found, it produces the error as an output. 
   
• Image Encryption System: It is a system where unauthorized users can’t access it because it encodes an image using an encryption algorithm. While transmitting digital images, encryption techniques implemented like AES (Advanced Encryption Technique) are needed to hide the actual image and reduce the chance of risk. It follows the step of dividing images randomly and uses secret keys which determine the encryption image blocks order. 

These were some amazing technologies on which you can build amazing projects in your final year. For more final year project ideas do refer to Computer Science Projects.

Biomedical Projects

 Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning

This paper presents an automatic content-based image retrieval (CBIR) system for brain tumors on T1- weighted contrast-enhanced magnetic resonance images (CE-MRI). The key challenge in CBIR systems for MR images is the semantic gap between the low-level visual information captured by the MRI machine and the high-level information perceived by the human evaluator. The traditional feature extraction methods focus only on low-level or high-level features and use some handcrafted features to reduce this gap. It is necessary to design a feature extraction framework to reduce this gap without using handcrafted features by encoding/combining low-level and high-level features. Deep learning is very powerful for feature representation that can depict low-level and high-level information completely and embed the phase of feature extraction in self-learning. Therefore, we propose a deep convolutional neural network VGG19-based novel feature extraction framework and apply closed- form metric learning to measure the similarity between the query image and database images. Furthermore, we adopt transfer learning and propose a block-wise fine-tuning strategy to enhance the retrieval performance. The extensive experiments are performed on a publicly available CE-MRI dataset that consists of three types of brain tumors (i.e., glioma, meningioma, and pituitary tumor) collected from 233 patients with a total of 3064 images across the axial, coronal, and sagittal views.

2WGAN-Based Synthetic Minority Over-Sampling Technique: Improving Semantic Fine- Grained Classification for Lung Nodules in CT Images

3Deep Belief Network Modeling for Automatic Liver Segmentation

4Classification of Breast Cancer Histology Images Using Multi-Size and Discriminative Patches Based on Deep Learning

5Convolutional Neural Network (CNN) Based Three Dimensional Tumor Localization Using Single X-Ray Projection

6Intrinsic Image Decomposition-Based Grey and Pseudo-Color Medical Image Fusion

7Multi-Resolution CNN and Knowledge Transfer for Candidate Classification in Lung Nodule Detection

8Brain MRI Image Classification for Cancer Detection Using Deep Wavelet Auto encoder- Based Deep Neural Network

9Lung Nodule Detection with Deep Learning in 3D Thoracic MR Images

10Skin Lesion Classification Using Convolutional Neural Network with Novel Regularizer

11A New Hybrid Algorithm for Retinal Vessels Segmentation on Fundus Images

12Multi-Modal Medical Image Fusion with Adaptive Weighted Combination of NSST Bands Using Chaotic Grey Wolf Optimization

13Diagnosis and Data Probability Decision Based on Non-Small Cell Lung Cancer in Medical System

14Robust Retinal Image Enhancement via Dual-Tree Complex Wavelet Transform and Morphology-Based Method

15Medical Image Retrieval Based on Convolutional Neural Network and Supervised Hashing

16An Improved Confidence Connected Liver Segmentation Method Based on Three Views of CT Images

17Analyzing the Dynamics of Lung Cancer Imaging Data Using Refined Fuzzy Entropy Methods by Extracting Different Features

18Studies on Different CNN Algorithms for Face Skin Disease Classification Based on Clinical Images

19Multi-Classification of Brain Tumor Images Using Deep Neural Network

20Fine-Grained Classification of Cervical Cells Using Morphological and Appearance Based Convolutional Neural Networks

21A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus Images

22Robust retinal blood vessel segmentation using hybrid active contour model

23Multi-objective based radiomic feature selection for lesion malignancy classification

24Discriminative Feature Learning with Foreground Attention for Person Re-identification

25Blood Cell Classification Based on Hyper spectral Imaging with Modulated Gabor and CNN