IEEE Python Projects 2024 2025 Machine Learning Projects, Deep Learning Projects, Artificial Intelligence Titles, Data Science Project Ideas for Final Year 2024 2025

Python Projects 2023 Machine Learning Projects, Artificial Intelligence, Deep Learning Projects title, Data Science project ideas for Final Year IEEE Projects 2023 – 2024 Ieee machine learning Projects Ieee machine learning Projects 

S.NO	DOMAIN	PROJECT TITLES	DOWNLOAD	DOWNLOAD	COST	DOWNLOAD
IXP2401	Blockchain	A Decentralized Voting system using Blockchain	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2402	Machine Learning	UPI Fraud Detection Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2403	Machine Learning	DeepFake Face Detection using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2404	Machine Learning	AI-based Learning Assistant Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2404	Machine Learning	Disaster Management with Sentiment and Earthquake/Tsunami Prediction System	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2405	Machine Learning	Prediction of the Electronic Gadget Addiction of Students Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2406	Machine Learning	FutureCrop: AI-Powered Price Prediction for Agri and Vegetable Markets	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2407	Machine Learning	Smart Career Advisor: A Machine Learning based Recommendation System	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2408	Machine Learning	Flood and Landslide Prediction using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2409	Machine Learning	Blood Group Detection using Image Processing and Fingerprint	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2410	Machine Learning	Alzheimer’s Disease Detection using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2411	Blockchain	Question Paper Leakage Prevention Using Blockchain	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2412	Machine Learning	Food Recognition and Calorie Estimation using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2413	Machine Learning + Deep Learning	AgriBot – An Intelligent Chatbot For Farmers With Crop And Disease Prediction	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2414	Deep Learning	Student Engagement Prediction in online Classes using Image Processing	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2415	Machine Learning	Cyberbullying Prediction Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2416	Blockchain	Student Certificate Validation Using Blockchain	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2417	Machine Learning	Secure Cyber Fraud App Detection Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2418	Machine Learning	Diabetic Retinopathy Prediction Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2419	Deep Learning	Oral Cancer Detection using Deep Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2420	Blockchain	Secure Banking Transactions Using Blockchain Technology	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2421	Machine Learning	AI-based Multi Disease Detection using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2422	Machine Learning	Blood Group Detection using Image Processing and Fingerprint	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2423	Machine Learning	Audio DeepFake Detection Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2424	Deep Learning	AI Car with Real-time detection of Damaged Road and Lane Detection	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2425	Deep Learning	Blood Cancer Detection using Deep Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2425	Blockchain	A Blockchain-Based Credible and Secure Education Data Management	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2426	Machine Learning	Innovative Flood and Landslide Prediction using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2427	Deep Learning	Heart Attack Risk Prediction using Retinal Eye Images	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2428	Machine Learning	Realtime Face Speech Emotion Recognition in Worker Stress Analysis	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2429	Machine Learning	Mental Health Detection Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2430	Machine Learning	Vitamin Deficiency Detection using Image Processing	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2431	Deep Learning	Intelligent Traffic System for Urban Conditions using Real-time Vehicle Tracking	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2432	Machine Learning	Medicine Overdose Prediction Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2433	Machine Learning	Election Results Prediction Using Machine Learning and Twitter	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2434	Blockchain	Patient Electronic Health Records using Block chain Security Framework	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP235	Machine Learning	Respiratory Disease Classification Using Lung Sounds with CNN-LSTM	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2436	Deep Learning	Breast Cancer Detection using Deep Learning Ultrasound Images	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2437	Blockchain	Secure Organ Donation using Blockchain Technology	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2438	Blockchain	Student Teacher Performance Prediction Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2439	Machine Learning	Predicting Poverty Level from Satellite Imagery	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2440	Machine Learning	Subjective Answer Evaluation using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2441	Machine Learning	PHISHSIM:  Phishing Website Detection With a Feature-Free Tool	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2442	Machine Learning	Train Delay Prediction using ML	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2443	Blockchain	Secure Supply chain Management using Blockchain	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2444	Deep Learning	Human Authentication using Walking Style	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2445	Machine Learning	Food Recognition and Calorie Measurement using Artificial Intelligence	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2446	Machine Learning	Parkinson’s Disease Detection Using Spiral Images (Hand Drawings)	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2447	Deep Learning	WildTrackAI – Applies Computer Vision to Animal Footprint Classification	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2448	Blockchain	Secure Land Registry System using Blockchain	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2449	Machine Learning	Medicinal Plant Classification using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2450	Machine Learning	Drug Recommendation System based on Sentiment Analysis of Drug Reviews using ML	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2451	Machine Learning	Stress Detection In IT Professionals by Image Processing and Artificial Intelligence	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2452	Machine Learning	Employee Attrition Prediction Using RNN	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
Importance of Artificial intelligence  Accordingly, In predictive analytics, companies, businesses, and healthcare professionals apply artificial intelligence, machine learning, and data mining to look at quiet records so as to decide conceivable patient results, for example, the chance of an exacerbating or Specifically improving well-being condition, or odds of acquiring an ailment in a person’s and group of the patient. In summary Artificial Intelligence much a useful solution to Improve overall computational processes. Similarly to Artificial Intelligence Data Science is Also an Emerging topic in recent Days.
IXP2214	Deep Learning	Diabetic Retinopathy Detection Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2215	Machine Learning	Employee Layoff Prediction using Recurrent Neural Network	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2216	Machine Learning	Fake Job Post Detection using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2217	Machine Learning	Car Price Prediction using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2109	Machine Learning	Potato Disease Detection using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2110	Deep Learning	Vehicle Speed Detection Using Deep Learning Approach	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2111	Machine Learning	Credit card Fraud Detection using Machine learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2112	Machine Learning	Stress Detection In IT Professional by Image Processing and Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2113	Machine Learning	Chronic Kidney Disease prediction using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2114	Deep Learning	A Deep Learning-Based Framework for Robust Traffic Sign Detection Under Challenging Weather Condition	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2115	Deep Learning	Brain Tumor Classifications using Deep learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2116	Deep Learning	Diagnosis of COVID-19 from Chest X-Ray Images Using Wavelets-Based Depthwise Convolution Network	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
Importance of Machine Learning In short Machine learning is an emerging field in computer science as it has given a new dimension to the concept of learning. Particularly By learning from past data, it emulates human intelligence in the system. In this case, Due to its self-adaptive capability and mathematical basis, machine learning has huge applications in healthcare, sentiment analysis, recommendation systems, natural language processing, information retrieval, gameplay, market analysis, text recognition, and computer vision. For this reason, Machine learning research was the most demanding research domain Accordingly.
IXP2117	Machine Learning	CRIME TYPE AND OCCURRENCE PREDICTION USING MACHINE LEARNING ALGORITHM	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2118	Machine Learning	Cyberbullying Detection on Social Networks Using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2119	Machine Learning	A Road Accident Prediction Model Using Data Mining Techniques	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2120	Machine Learning	A Systematic Review of Predicting Elections Based on Social Media Data Research Challenges and Futures	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2121	Machine Learning	A Neural Based Approach for Detecting the Situational Information From Twitter During Disaster	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2122	Machine Learning	WELFake Word Embedding Over Linguistic Features for Fake News Detection	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2123	Machine Learning	Detecting Fake Reviews Using Multidimensional Representations With Fine Grained Aspects Plan	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2124	Deep Learning	Data Fusion based Two-stage Cascade Framework for Multi-Modality Face Anti-Spoofing	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2125	Machine Learning	Fake Profile Detection for Matrimonial Sites	ABSTRACT	BASEPAPER	Rs.3000	VIDEO
IXP2126	Machine Learning	Heart Disease Prediction System using CNN	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2127	Machine Learning	Multiplex Regulation System With Personalised Recommendation Using ML	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2128	Deep Learning	Multi Crop Convolutional Neural Networks for Fast Lung Nodule Segmentation	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2129	Deep Learning	Chest Xray Pulmonary Tuberculosis Detection using Deep learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
Importance of Deep Learning To begin with, Deep Learning (DL) a type of ML solves the problems that were unsolvable with machine learning. In short Deep learning uses neural networks to increase computational work and provide accurate results. Some of the incredible applications of deep learning are NLP, speech recognition, and face recognition. For this reason, DL in collaboration with IoT, is witnessing revolutionary innovations.
IXP2130	Machine Learning	Cyclone Prediction and Rainfall Prediction using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2131	Machine Learning	Intrusion Detection System Using Machine Learning	ABSTRACT	BASE PAPER	Rs.4000	VIDEO
IXP2132	Machine Learning	Fraud App Detection Using Machine Learning	ABSTRACT	BASE PAPER	Rs.4000	VIDEO
IXP2133	Machine Learning	Lung Cancer Detection using Machine Learning	ABSTRACT	BASE PAPER	Rs.4000	VIDEO
IXP2134	Blockchain	EHRChain: A Blockchain Based EHR System Using Attribute-Based and Homomorphic Cryptosystem	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2135	Machine Learning	House Price Prediction using Machine Learning	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2136	Deep Learning	Blockchain based solution to improve the Supply Chain Management in Indian agriculture	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2137	Deep Learning	Drowsiness detection system based on Eye State Analysis	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2138	Deep Learning	DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
IXP2139	Machine Learning	Agricultural Crop Recommendations based on Productivity and Season	ABSTRACT	BASEPAPER	Rs.4000	VIDEO
		More Titles will be updated Regularly
		Machine learning projects for final year 2023 2024 Data Science projects for final year 2023 2024
Importance of Data Science As a matter of fact, Data Science (DS) has matured as a field of basic and applied research in computer science in general and e-commerce in particular. Although,  some of the recent approaches and architectures where data mining has been applied in the fields of e-commerce and e-business. Comparatively the dominant goal of DM  is the generation of non-obvious yet useful information for decision-makers from very large databases. The various mechanisms of this generation include abstractions, aggregations, summarizations, and characterizations of data as proposed by the Authors. Correspondingly these forms, in turn, are the result of applying modeling techniques from the diverse fields of statistics, artificial intelligence, database management, and computer graphics.

Python Projects source code 2023 2023

IEEE papers on Python Machine Learning final year projects IEEE Machine learning projects for final year with source code in Python IEEE projects for CSE 2023 2024

What is Machine Learning?

Basically, An ML model is defined as a computer-intensive mechanism and applies resampling and iterative methodologies for classification approaches. Especially  ML approaches are considered with optimal subset selection and eliminate the issues of classical classifiers like over-fitting as well as distributional demands of parameters. Following ML technologies that have emerged in computer science with logic and basic mathematics, statistics, as ML approaches do not estimate the group, features rather it is initialized with an arbitrary group separator and tunes frequently till satisfying the classification groups. Significantly ML examines the tuning variables and individual ML functions that became unstable, Balanced against which makes a suitable process. Furthermore, As the non-statistical nature is embedded, overall these approaches can apply the data in various formats like nominal data that generates maximum classification accuracies.

Project on Machine Learning 

In this Section Specifically, we have discussed about some of the projects on Machine Learning with current trends.

Predicting Poverty Level from Satellite Imagery

Determining the poverty levels of various regions throughout the world is still crucial in identifying interventions for poverty reduction initiatives and directing resources fairly. Generally, reliable data on global economic livelihoods is hard to come by, especially for areas in the developing world, hampering efforts to both deploy services and monitor/evaluate progress. However, the current challenge in this domain is that agencies across the world that predict income levels take a huge amount of time to do the same.

Instead of a Manual Human Taking process, This project proposes to use satellite images to detect economic activity and, as a result, estimate poverty in a location. lastly, A Recurrent neural network is trained to learn various developmental parameters like rooftop type, source of lighting, proximity to water sources, Agriculture Areas, Road Structure, and Industrial Areas. Likewise, it will estimate the poverty level of each Area using Satellite Images. particularly it will cost you less amount as well comparatively less time as well.

Phishing Website Monitoring Using ML

In this project, we propose a feature-free method for detecting phishing websites correspondingly based on a similarity measure that computes the similarity of two websites by compressing them, thus eliminating the need to perform any feature extraction. Additionally, It also removes any dependence on a specific set of website features. Altogether this method examines the HTML of webpages and computes their similarity with known phishing websites during testing phases, in order to classify them.

Furthermore, We use the Furthest Point First algorithm to perform phishing prototype extractions, in order to select instances that are representative of a cluster of phishing web pages. Identically We also introduce the use of an incremental learning algorithm as a framework for continuous and adaptive detection without extracting new features when concept drift occurs. Lastly, On a large dataset, our proposed method significantly outperforms previous methods in detecting phishing websites, with an AUC score of 98.68%, a high true positive rate (TPR) of around 90%, while maintaining a low false positive rate (FPR) of 0.58%. Particularly Our approach uses prototypes, eliminating the need to retain long-term data in the future, and simultaneously is feasible to deploy in real systems with a processing time of roughly 0.3 seconds.

Food Recognition and Calorie Measurement using Machine Learning

Presently This is one of the projects particularly to discuss the relationship between nutritional ingredients identification in food and inspecting Calories through Machine Learning models to perform the data analysis, Significantly the experiments on real-life datasets show that our method improves the performance with efficient accuracy . Specifically, Our system will recommend food for some Different Age groups. Subsequently, Our work is able to identify the Nutrition that we may get affected by lacking certain nutritional ingredients in our body and recommends the food that can benefit the rehabilitation of those Age Groups. Thereafter To achieve high accuracy and low time complexity, the proposed system was implemented using CNN Machine Learning models. Lastly, The model, when trained convolutionally, generates the natural image samples which give a better broad statistical structure of the natural images as compared with comparatively existing parametric generative methods.

Train Delay Prediction using Machine Learning

Eventually Delay prediction is a process of estimating delay probability based on formerly known data at a given checkpoint and is typically measured via arrival (departure) delay. Furthermore the key to making delay predictions based on actual operational data involves establishing the relationship between train delays and various characteristics of a railway system. Henceforth this provides a basis for the operator’s scheduling decision Train delay is a significant problem that negatively impacts the railway industry and costs billions of dollars each year. Simultaneously In this project we have used Train delay dataset from IRTC to predict Train delays. Specifically  We have used Faster RCNN algorithm to predict flight departure delay and thereupon our model can identify which features were more important when predicting Train delays.

Blood Grouping Detection Using Image Processing

Basically, there is worldwide demand for an affordable Blood Group measurement solution, although this is a particularly urgent need in developing countries. Altogether Image Processing, which is the most penetrated device in both rich and resource-constrained areas, would be a suitable choice to build this solution. Comparatively This Project proposes a noninvasive Blood Group measurement process.  Also, it compared the variation in data collection sites, biosignal processing techniques, theoretical foundations, photoplethysmogram (PPG) signal and features extraction process, Image Processing algorithms, and Detection models to calculate Blood Groups. Especially This analysis was then used to recommend realistic approaches to build an Image Processing-based point-of-care tool for Blood Group measurement in a non-invasive manner. Certainly, This project proposes approaches for blood Group measurement with the aim of recommending data collection techniques, signal extraction processes, feature calculation processes, and Image Processing algorithms for developing a noninvasive Blood Group estimation using an Image.

Parkinson’s Disease Detection Using Spiral Images

Correspondingly Parkinson’s Disease (PD) is a progressive neurodegenerative disorder emphatically, which is characterized by  Various symptoms. Furthermore, the progressive neurodegenerative disorder affects the nervous system in the elderly, which is characterized by motor symptoms such as tremors, rigidity, slowness of movement, and problems with gait. Obviously, In this work, an attempt has been made to classify the spiral images of healthy control and Parkinson’s disease subjects using deep-learning neural networks. Particularly The Vision-based Convolutional Neural Network architecture is used to refine the diagnosis of neurodegenerative disorder disease.

Nevertheless, This project proposes a Vision-Based novel deep learning architecture for neuro-generative disorder screening. obviously, this project, analysis of Spiral images for discrimination of healthy control and NDD (Neurodegenerative disorder) subjects is attempted using the CNN model. The proposed FAST-RCNN exploits Feature Extraction to tackle multi-view data from the Spiral Image data. significantly training, the proposed model employs a data enhancement technology called SCI-KIT’s Image Data Generator API on multi-view data.

Drug Recommendation System based on Sentiment Analysis of Drug Reviews using Machine Learning

Since the coronavirus has shown up, the inaccessibility of legitimate clinical resources is at its peak, previously like the shortage of specialists and healthcare workers, secondly lack of proper equipment and medicines, etc. Specifically, The entire medical fraternity is in distress, which results in numerous individuals’ demise. unlike Due to unavailability, individuals started taking medication independently without appropriate consultation, making their health condition worse than usual. Identically As of late, machine learning has been valuable in numerous applications, and there is an increase in innovative work for automation.

Meanwhile, This project intends to present a drug recommender system that can drastically reduce specialists’ heap. Regardless In this research, we build a medicine recommendation system that uses patient reviews to predict the sentiment using various vectorization processes like Bow, TF-IDF, Word2Vec, and Manual Feature Analysis, which can help recommend the top drug for a given disease by different classification algorithms. specifically, The predicted sentiments were evaluated by precision, recall, F1 score, accuracy, and AUC score. whereas The results show that classifier DNN using TF-IDF vectorization outperforms all other models with 98% accuracy.

Stress Detection In IT Professionals by Image Processing and Machine Learning

Significantly The main motive of our project is to detect stress in IT professionals using vivid Machine learning and Image processing techniques. obviously, Our system is an upgraded version of the old stress detection systems which excluded live detection and personal counseling but this system comprises of live detection and periodic analysis of employees and detects physical as well as mental stress levels in his/her by providing them with proper remedies for managing stress by providing survey form periodically. Moreover, Our system mainly focuses on managing stress and making the working environment healthy and spontaneous for the employees and furthermore it getting the best out of them during working hours.

Henceforth The proposed System Machine Learning algorithms like KNN classifiers are applied to classify stress. Following Image Processing is used at the initial stage for detection, the employee‟s image is given by the browser which serves as input. further, In order to get an enhanced image or to extract some useful information from it image processing is used by converting image into digital form and performing some operations on it. Generally By taking input as an image and output may be image or characteristics associated with that images. The emotion are displayed on the rounder box. The stress level indicated by Angry, Disgusted, Fearful, Sad.

Human Authentication using Gait Recognition (Walking Style)

Evidently, Biometric identification like fingerprints, retina, palm, and voice recognition needs the subject’s permission and physical attention. Correspondingly Human Gait recognition works on the gait of walking subjects to identify people without them knowing or without their permission. Basically, The purpose of this Project is to detect humans based on their Waling styles. We first extract the gait features from image sequences using the Feature Module. Features are then trained based on the frequencies of these feature trajectories, from which recognition is performed.

Gait recognition is the process where the features of human motion are automatically obtained/extracted and later these features enable us to authenticate the identity of the person in motion. Besides As with other pattern recognition techniques, the gait recognition technique also involves 2 stages: Firstly Information is derived from human locomotion in the first stage i.e. feature extraction stage. Formerly In the next stage, i.e. the recognition stage, a standard similarity computation technique (Incremental Component Analysis) is used to obtain results for being a match or a mismatch.

Decentralized Voting system using Blockchain

Certainly, Electronic voting or e-voting has been used in varying forms since the 1970s with fundamental benefits over paper-based systems such as increased efficiency and reduced errors. However, there remain challenges to achieving widespread adoption of such systems, especially with respect to improving their resilience against potential faults. Generally, Blockchain is a disruptive technology of the current era and promises to improve the overall resilience of e-voting systems. Likewise, This project presents an effort to leverage the benefits of blockchain such as cryptographic foundations and transparency to achieve an effective scheme for e-voting.

Moreover, The proposed scheme conforms to the fundamental requirements for e-voting schemes and achieves end-to-end verifiability. The paper presents details of the proposed e-voting scheme along with its implementation using the Multichain platform. Obviously, The project presents an in-depth evaluation of the scheme which successfully demonstrates its effectiveness to achieve particularly an end-to-end verifiable e-voting scheme. Ieee machine learning Projects

Diabetic Retinopathy Detection Using Machine Learning

Diabetic Retinopathy is the most common cause of vision loss among people particularly diabetes and the leading cause of vision impairment and blindness among working-age adults. Secondly, By using a certain algorithm the retinal image from the user is fed into the system. significantly The blood vessels are extracted from the image then it is pre-processed by filtering and segmentation process. Rather It is followed by fractional edge reduction which is used for the feature extraction and by using a Faster retinal convolutional neural network algorithm to automate the diagnosis process. It improves the resultant accuracy and by this classification technique,overall we can achieve high accuracy. Ieee machine learning Projects