Aim: To detect the COVID-19 using x-ray images by using Convolutional neural network. Abstract: The Corona-virus 2019(COVID-19), which first occurs in Wuhan city of China in December 2019, spread quickly around the world and became a plague. Due to the r..
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 disasters. Since most insect species are extremely similar, insect detection on field crops, such as rice, soybean and other crops, is more challenging than g..
Aim: To recognize the real time facial expression using Deep learning technique.Abstract: In today’s world, there is a tremendous increase in usage of machinery. The world needs machines to understand humans and interpret ac..
Aim: To automate the detection of presence of ships and to classify the types of ships available in the given Image. Synopsis: The detection of inshore and offshore ships is an essential task for a large variety of applications in both military and civilian fields. For example..
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 2.7million people and caused over 180..
Aim: Optical character recognition (OCR) can be used for the online retrieval of the printed material such as medical documents, forms, or applications for retrieving valuable information that was available in the printed documents. Deep learning approaches have been used to solve natural langua..
Aim: To efficient CNN based system for fire detection in videos captured in uncertain surveillance scenariosSynopsis: Vision based fire detection framework has lately picked up popularity when contrasted ..
Automatic Detection and Monitoring of Diabetic Retinopathy Using Efficient Convolutional NeuralNetworks
Aim: This paper aim to detect the diabetic disease identification using deep learning methods. Abstract: Diabetic Retinopathy is a complication of diabetes that is caused due to the changes in the blood vessels of the retina and is one of the leading causes of blindness in th..
Aim: As the house price prediction is vital for both the Ill-being of the public and the economic development, many experts in different research fields have explored and predicted it with the machine-learning strategies. Because the price is susceptible to multiple factors, it..
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..
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. ..
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..
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..
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..