Papers by Dr.Jagannath Jadhav
Intelligent Data Communication Technologies and Internet of Things, 2019
Remote sensing (RS) has become one of the vital approaches to get the information directly from t... more Remote sensing (RS) has become one of the vital approaches to get the information directly from the earth’s surface. In recent years, with the event of environmental informatics, RS information has contend a crucial role in several areas of analysis, like atmosphere science, ecology, soil pollution, etc. When monitoring, the multispectral satellite data problem are vital once. Therefore, in our analysis, automatic segmentation has aroused a growing interest of researchers over the past few years within the multispectral RS system. To beat existing shortcomings, we provide automatic semantic segmentation while not losing significant information. So, we use SOM for segmentation functions. Additionally, we’ve got planned a particle swarm improvement (PSO) algorithmic rule for directly sorting out cluster boundaries from SOM. The most objective of this work is to get a complete accuracy of over eighty fifth (OA> 85%). Deep Learning (DL) could be a powerful image process technique, together with RS image.
Materials Today: Proceedings, 2021
Towards the improvement of predicting and analyzing the infection transmission, a novel CNN (Conv... more Towards the improvement of predicting and analyzing the infection transmission, a novel CNN (Convolution Neural Network) based Covid Infection Transmission Analysis (CNN-CITA) is presented in this article. The method works based on both GIS data set and the Covid data set. The method reads all the data from the data sets. From the remote sensing data, the method extracts different climate conditions like temperature, humidity, and rainfall. Similarly from Global Information System data set, the locations of the peoples are fetched and merged. The merged data has been split into number of time frame, at each condition, the data sets are merged. Such merged data has been trained with deep learning networks which support the search of person location and mobility. Based on the result and the data set maintained by the governments, the infection transmission rate has been measured on region basis. In each region of movement performed by any person, the method computes the infection Transmission Rate (ITR) in two time window as before and after. According to the infection rate and ITR value of different region, a subset of sources are selected as vulnerable sources. The method produces higher performance in predicting the vulnerable sources and supports the reduction of infection rate. Index Terms: CNN, CNN-CITA, Regional Transmission, Infection Rate, ITA, ITS, GIS, Remote Sensing Data.
2020 Fourth International Conference on Inventive Systems and Control (ICISC), 2020
Remote sensing field has become very important and essential approaches to acquire data straightf... more Remote sensing field has become very important and essential approaches to acquire data straightforwardly from the earth’s surface. The multi-layered DL design, that aims to reason vegetation and crop sorts supported multi-source multiple satellite images. The premise of the design is to associate the Unsupervised Neural Network (UNN), won't segment optical images and recovers missing information because of clouds and shadows. Additionally, the planned ways permit getting hybrid cluster segmentation and classification precision compared to obtainable ways. Simulation results are conferred to demonstrate the effectiveness of the planned technique applied to a synthetic and real-time dataset.
The development of new technologies, human nature, and food activities are completely against wit... more The development of new technologies, human nature, and food activities are completely against with nature in recent days. Due to this uncertainty, the new pandemic covid-19 has outbreak globally and spoiledthe human life. In this situation, the disease also has improved as a new modified version of influenza like Covid 19 (2.0). So, the Analysis of features becomes mandatory to identify the diseases based on big data analysis. Similarly, most people suffering from diabetes could not have a correct prediction to take proper treatments. Many health care suggestions and treatment handling methods do not predict the right information at the correct time to make a diagnosis. There is no premature process for the treatment based on non-predicted results. Hence, an Adaptive Surf Scale Feature Selection (SSFS) and Sigmoid Recurrent Neural Network Classification (SRNN) is proposed for improving the early risk prediction against the covid. Initially, preprocessing is carried out to verify the...
International journal of engineering research and technology, 2018
Speech recognition is a process where a speech file is recognized against the stored speech data ... more Speech recognition is a process where a speech file is recognized against the stored speech data set. Speech recognition is the ultimate goal concerned with science, technology, and engineering of discovering patterns and extracting potentially useful or interesting information automatically or semi-automatically from speech data. It analyzes the data set according to the classifier and predicts results accordingly. In this scenario, a predicted output is one which matches the most with the data base. Several kinds of classifier have been used in this scenario. This paper represents different sections of the speech recognition process and classification methods are also discussed. This paper aimed to design an efficient system for extracting useful information from speech signal and use the same information to design the classifier which is capable of differentiating male and female voices.
Journal of Information Technology and Digital World, 2020
Remote sensing imaging (RSI) technology has recently been identified as an effective photogrammet... more Remote sensing imaging (RSI) technology has recently been identified as an effective photogrammetric data acquisition platform to rapidly provide high resolution images due to its profitability, its ability to fly at low altitude and the ability to analysis in dangerous areas. The various kinds of classification techniques are have been used for flood extent mapping for finding the flood affected region, but based on the color region based analysis the classified hazardous area has very complex. Due to over the above issues in this work there significant enhancements have appeared in the classification of remote sensing images using Contiguous Deep Convolutional Neural Network (CDCNN).In the flood detection system the four different kinds of process like preprocessing, segmentation, feature extraction and the Contiguous Deep Convolutional Neural Network (CDCNN) has been executed for identifying the flood defected region. This works also investigates and compare with the possible met...
Mathematical Models in Engineering, 2018
Automatic semantic segmentation has expected increasing interest for researchers in recent years ... more Automatic semantic segmentation has expected increasing interest for researchers in recent years on multispectral remote sensing (RS) system. The agriculture supports 58 % of the population, in which 51 % of geographical area is under cultivation. Furthermore, the RS in agriculture can be used for identification, area estimation and monitoring, crop detection, soil mapping, crop yield modelling and production modelling etc. The RS images are high resolution images which can be used for agricultural and land cover classifications. Due to its high dimensional feature space, the conventional feature extraction techniques represent a progress of issues when handling huge size information e.g., computational cost, processing capacity and storage load. In order to overcome the existing drawback, we propose an automatic semantic segmentation without losing the significant data. In this paper, we use SOMs for segmentation purpose. Moreover, we proposed the particle swarm optimization techni...
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Papers by Dr.Jagannath Jadhav