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A Rotational Libra R-CNN Method for Ship Detection
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..
ATT Squeeze U-Net A Lightweight Network for Forest Fire Detection and Recognition
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..
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..
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. ..
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 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..
Driver-Drowsiness Detection System Using Facial Features
Aim: This paper aim to detect Real time driver's fatigue state using Convolutional Neural Network (CNN) Synopsis: Accidents are more due to the driver’s drowsiness; it has been recorded that more than 40% of chances that acciden..
Efficient Classification Of Diabetic Retinopathy Using Binary Cnn
Aim: To detect the diabetic retinopathy disease in the earlier stage using Deep learning method Synopsis: Diabetic Retinopathy is a disease that can lead to partial or complete blindness. Research shows that it contributes around 5 percent of the total cases of blindness. Usually it takes about two weeks for the diagnosis of disease; time and money..
Human Activity Recognition Through Ensemble Learning of Multiple Convolutional Neural Networks
Aim: This paper aim to classify the different types of videos using deep learning framework with convolution neural network (CNN) Abstract: Video classification has been extensively researched in comp..
Krushi Sahyog: Plant disease identification and Crop recommendation using Artificial Intelligence
Aim: To detect the plant leaf disease and to recommend the crop using Machine and Deep learning. Abstract: India is one of the leading countries worldwide in terms of farm output. Even after being a leading ..
Lung Lesion Localization of COVID-19 From Chest CT Image: A Novel Weakly Supervised Learning Method
Aim: To detect the COVID-19 using CT 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 an..
Plant Disease Detection and Classification by Deep Learning: A Review
Aim: To detect the plant leaf diseases using convolutional neural network for high accuracy detection.Synopsis: Identification of leaf disease is very difficult in agriculture field. If identification is incorrect then there is a huge ..
Real-Time Prediction of Taxi Demand Using Recurrent Neural Networks
Aim:To predict the high demand need of pickup location for taxi services based on their previous history. Synopsis:The service industry is booming for the last couple of years and it is expected to grow in the near future. One of the important natures of the business is the serve the customer. To effectively utilize the resource at hand is..
Ship Detection and Segmentation using Unet
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. The sur..