Brain Tumor Detection and Classification Using Convolutional Neural Network (CNN)
Aim: To detect and identify the Brain Tumor using Deep-Learning techniques.Abstract: Medical image processing is that the one among the foremost demanding and promising field nowada..
Brain Tumor Identification and Classification of MRI images using deep learning techniques
Aim: To detect and identify the Brain Tumor using Deep-Learning techniques Abstract:Brain is the controlling unit of human body. It regulates the functions such as memory, vision, hearing, knowledge, personality, problem solving etc. The main reason for brain tumors is the uncontrolled development of brain cells. In medical practices..
Breast Cancer Detection Using Extreme Learning machine Based on Feature Fusion with CNN Deep Features
Aim: To classify benign and malignant breast masses using K Nearest Neighbor based on Feature Fusion with CNN Deep Features.Synopsis: A computer-aided diagnosis (CAD) system based on mammogram..
Classifying Swahili Smishing Attacks for Mobile Money Users: A Machine-Learning Approach
Aim: Massive adoption of mobile money in countries, the global transaction value of mobile money exceeded $2 billion in 2021. Projections show transaction values will exceed $3 billion by the end of 2022, Spammers use Smishing (SMS Phishing) messages to trick a mobile money use..
Comparison of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Aim: To apply machine learning techniques result in improving the accuracy in the prediction of Chronic Kidney Disease.Abstract: Chronic kidney disease (CKD) is the serious medical condition where the kidneys are damaged and blood cannot be filtered. In the end-stag..
Convolution neural network based enhanced computerized Technique for brain tumour detection
Aim: To detect and identify the Brain Tumor using Deep-Learning techniquesSynopsis: Brain is the controlling unit of human body. It regulates the functions such as memory, vision, hearing, knowledge, personality, problem solving etc. ..
Covid-19 Classification and Detection Model using Deep Learning
Aim: To detect the COVID-19 using x-ray images by using Convolutional neural networkAbstract: The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world..
Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms
Aim: People can use credit cards for online transactions as it provides an efficient and easy-to-use facility.With the increase in usage of credit cards, the capacity of credit card misuse has also enhanced. Credit card frauds cause significant financial losses for both credit card holders..
Crop Yield Prediction based on Indian Agriculture using Machine Learning
Aim: To be precise and accurate in predicting crop yield and deliver the end user with proper recommendations about required fertilizer ratio based on soil parameters.Abstract India is the land of agriculture and it is the major source of economy.70% of Ind..
Crop Yield Prediction Using Random Forest Algorithm
Aim: Predict the crop type and price of the crop using machine learning methodology with accurate results.Abstract India is the land of agriculture and it is the major source of economy. 70% of..
Cursive Text Recognition in Natural Scene Images Using Deep Convolutional Recurrent Neural Network
Aim: Text recognition in natural scene images is a challenging problem in computer vision. Text recognition in natural scene images is more complex due to variations in text size, colors, fonts, orientations, complex backgrounds, occlusion, illuminations and uneven lighting condition..
Deep Convolutional Neural Network for Fire Detection
Aim: To efficient RCNN based system for fire detection in videos captured in uncertain surveillance scenarios Synopsis: Vision based fire detection framework has lately picked up popularity when contrasted with cus..
Deep Learning based Automatic Multi-Class Wild Pest Monitoring Approach using Hybrid Global and Local Activated Features
Aim: To detect and classify large-scale multi-class pest using Convolution Neural Network. Synopsis: Regarding the growth of crops, one of the important factors affecting crop yield is insect..
Deep Learning-Based Workers Safety Helmet Wearing Detection on Construction Sites Using Multi-Scale Features
Abstract: Due to a lack of knowledge about safety helmets, accidents and injuries on construction sites are now increasingly common. Worker supervision by hand is challenging and ineffective. Workers often take off the helmets because of weak security-conscious and discomfort, then ..
Deep Neural Architecture for Face mask Detection on Simulated Masked Face Dataset against Covid-19 Pandemic
Aim: To apply the Deep Learning techniques based on convolution neural network improving the face mask detector accuracy.Synopsis: The corona virus disease 2019 (COVID-19) has globally infected over..