Characterizing and Countering Communal Micro blogs During Disaster Events

Aim: The objective of this project is to develop a system to identify the tweet harbor hatred in micro blogs during disaster events. Existing System: The existing system uses sentiment analysis technique to identify the sentiment of the tweet. However this is not sufficient to identify the anti-social messages. The sentiment analysis might give the […]

IoT-Guard: Event-Driven Fog-Based Video Surveillance System for Real-Time Security Management

Aim: To design and implement a distributed Internet of Things framework called IoT-guard an efficient resource constrained methodology to prevent and predict crime events in a smart home environment. Existing System: In existing system various cyber-physical systems widely adopt the use of intelligent video surveillance, for automatic and accurate identification of events and objects in […]

Nearshore Ship Detection on High-Resolution Remote Sensing Image via Scene-Mask R-CNN

Aim: To automate the detection of presence of ships and to classify the types of ships available in the given Image. Existing System: Computer-aided ship detection methods greatly free up human resources and typically include two steps: extracting image features, and then using classifiers for classification and localization. These methods can produce stable results under […]

A Novel Stream Clustering Framework for Spam Detection in Twitter

Aim: The project is to classify spam tweets based on twitter account and content based features on twitter handles. Existing System: DenStream was promoted by the proposed framework, called here as INB-DenStream. To show the effectiveness of INB-DenStream, state-of-the-art methods such as DenStream, StreamKM++, and CluStream were applied to the Twitter datasets and their performance […]

Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural Networks

Aim: To detect the apple leaf diseases using convolutional neural network for high accuracy detection Existing System: In recent years, with the popularization of digital cameras and other electronic devices, automatic plant disease diagnosis has been widely applied as a satisfactory alternative. Nevertheless, in most cases, traditional machine learning approaches such as support vector machine […]

Efficient Fire Detection for Uncertain Surveillance Environment

Aim: To efficient CNN based system for fire detection in videos captured in uncertain surveillance scenarios Existing System: To detect fire, researchers have presented both traditional and learned representation based fire detection methods. In literature, the traditional methods use either color or motion characteristics for fire detection. For instance, [9-16] used color features for fire […]

Real-time Credit Card Fraud Detection Using Machine Learning

Aim: To detect the real time credit card fraud transaction using machine learning algorithms. Existing System: The obtained results are compared with the results of existing models within the same domain and found to be improved. The data of credit card fraud transactions data collected from the kaggle is used to discover patterns with Neural […]

Training Cascade Compact CNN With Region-IoU for Accurate Pedestrian Detection

Aim: To improve the Pedestrian detection rate and the localization accuracy using Cascade Compact CNN Existing System: R-CNN analysis shows that localization error and background error are still the two main errors for Faster R-CNN based detectors. In the following sections, the proposed approach will deal with these two types of errors by introducing a […]