Pair wise sequence alignment methods are used to find the best-matching pair wise local or global... more Pair wise sequence alignment methods are used to find the best-matching pair wise local or global alignments of two query sequences. Protein sequence alignment is one of the crucial tasks of computational biology which forms the basis of many other tasks like protein structure prediction, protein function prediction and phylogenetic analysis. In this paper we made a study on Pair Wise Local alignment and consider:(1) what sorts of alignment should be considered (2) the scoring system used to rank alignments (3) the algorithm used to find optimal (or good) scoring alignments and scoring measurements such as Bayesian approach, Classical approach (4) the statistical methods used to evaluate the significance of an
Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems
The smart system integrates cloud computing and mobile computing, also known as mobile cloud comp... more The smart system integrates cloud computing and mobile computing, also known as mobile cloud computing. This smart system helps monitor the vehicle's health condition on any device, i.e., platform-independent. Using machine learning algorithms, the smart system helps predict vehicle health and maintain the vehicle's and the driving person's safety. The cloud computing used to deploy this smart system for monitoring the vehicle condition is the Google Cloud Platform. Google Cloud Platform provides various services like Computing and Hosting, Networking, Storage, etc., which help deploy and host web applications on Google Cloud using multiple services. One of the best securities is achieved using the Google Cloud Platform. Several layers are encrypted with specially designed algorithms for the safety of the customer data and applications. Google Cloud Platform helps provide data integrity, making it better for storing all the data. It also provides Denial of Service protec...
Learning and Analytics in Intelligent Systems, 2019
Developing assistive systems for visually challenged people is an active area of research in comp... more Developing assistive systems for visually challenged people is an active area of research in computer vision community. Such system provides a medical assistive tool to take the correct medicine at the right time as prescribed by the doctor and makes visually challenged people to live independently for their day to day activities. Many prototypes were developed to deal with misidentification of medicines but are incapable of determining exact pill picked by the person. This paper presents an automated system where feature extraction is done to recognize the pills based on structural, texture and Hu moments. If the pill is picked from the medicine box, the label present on the pill is considered for Text Recognition. Pill label and expiry date are extracted from the label and classified using Convolutional Neural Network (CNN) and is converted to speech. This audio is produced to indicate the person about the medicine picked. Experimental results proved that our system is better than...
2022 International Conference on Electronics and Renewable Systems (ICEARS)
Cloud computing is one among the most crucial commercial technologies nowadays. It offers a diver... more Cloud computing is one among the most crucial commercial technologies nowadays. It offers a diverse range of services. One of the most exciting and important procedures in cloud computing is virtual machine installation (VMP). Virtual Machine Placement uses evolutionary computing to lower energy consumption while lowering the total number of physical servers that are currently in use. By examining the ant colony system’s (ACS) promising performance for combinatorial issues, Order Exchange and Ant Colony System OEMACS, an approach based on ACS finds solution by combining order exchange and migration local search strategies, was developed (Order exchange and Migration Ant Colony System). From a global optimization standpoint, The OEMACS algorithm is capable of significantly lowering the active servers in number and is used for virtual machine assignment. It also aids in the reduction of the number of active servers that are underutilized. In OEMACS, artificial ants are guided to the best feasible solution using the pheromone deposition method. It also arranges virtual machines in such a way that resource waste and power consumption are reduced. On servers with homogenous and heterogeneous VM sizes, this strategy is used. OEMACS surpasses some of the previously utilized algorithms, such as standard heuristics and other evolutionary-based techniques, according to the findings.
Now-a-days Image Processing has been the most interested subject for research. This paper present... more Now-a-days Image Processing has been the most interested subject for research. This paper presents the idea of recognizing the characters in digital image using Optical Character Recognition. The Optical Character Recognition process involves several aspects such as segmentation, feature extraction and classification. MATLAB provides a variety of functions that way providing the capabilities of developing applications and new algorithms in the field of image processing. This paper shows how to use MATLAB and its image processing toolbox functions in order to recognize characters in an image. We implement this using MATLAB for segmentation using edge detection, identification of characters, and storing the vector of characters. Optical Character Recognition (OCR) service enables application to retrieve the text that appears in a photograph. We have to first preprocess the image and image extraction as followed to find characters in a photograph. The resulting vector can be used in ma...
2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)
Rapid increase in urban settlements has caused a tremendous effect on natural deposits and habita... more Rapid increase in urban settlements has caused a tremendous effect on natural deposits and habitat. A perfect blueprint is needed for organizing the settlements without degrading the living standards. With the developed spatial technology, good quality of remote sensing data is now available. Using satellite images, change can be detected between two temporal images of the same scene. This change detection helps in the proper management of development proceedings. Exiting machine learning algorithms for change detection uses hand crafted features that may result to over-fitting problems. This paper proposes deep learning based methodology to detect the change in urban landscapes especially buildings. The proposed methodology involves a feature extractor complemented by an attention mechanism to capture the multi-scale dependencies between two pixels taken from two temporal images. With this methodology, both temporal and spatial features are taken into consideration in finding change detection.
Advances in Multimedia and Interactive Technologies
Object recognition and classification (human beings, animals, buildings, vehicles) has become imp... more Object recognition and classification (human beings, animals, buildings, vehicles) has become important in a surveillance video situated at prominent areas such as airports, banks, military installations etc., Outdoor environments are more challenging for moving object classification because of incomplete appearance details of moving objects due to occlusions and large distance between the camera and moving objects. As such, there is a need to monitor and classify the moving objects by considering the challenges of video in the real time. Training the classifiers using feature based is easier and faster than pixel-based approaches in object classification. Extraction of a set of features from the object of interest is most important for classification. Textural features, color features and structural features can be chosen for classifying the object. But in real time video, object poses are not always the same. Zernike moments have been shown to be rotation invariant and noise robus...
Optoelectronics in Machine Vision-Based Theories and Applications
Object recognition and classification has become important in a surveillance video situated at pr... more Object recognition and classification has become important in a surveillance video situated at prominent areas such as airports, banks, military installations, etc. Outdoor environments are more challenging for moving object classification because of incomplete appearance details of moving objects due to illumination changes and large distance between the camera and moving objects. As such, there is a need to monitor and classify the moving objects by considering the challenges of video in the real time. Training the classifiers using feature-based approaches is easier and faster than pixel-based approaches in object classification. Extraction of a set of features from the object of interest is most important for classification. Viewpoint and sources of light illumination plays major role in the appearance of an object. Abrupt transitions are identified using Chi-square and corners are detected using Harris corner detection. Silhouettes are captured using background subtraction and ...
Pair wise sequence alignment methods are used to find the best-matching pair wise local or global... more Pair wise sequence alignment methods are used to find the best-matching pair wise local or global alignments of two query sequences. Protein sequence alignment is one of the crucial tasks of computational biology which forms the basis of many other tasks like protein structure prediction, protein function prediction and phylogenetic analysis. In this paper we made a study on Pair Wise Local alignment and consider:(1) what sorts of alignment should be considered (2) the scoring system used to rank alignments (3) the algorithm used to find optimal (or good) scoring alignments and scoring measurements such as Bayesian approach, Classical approach (4) the statistical methods used to evaluate the significance of an
Computational Intelligence and Machine Learning Approaches in Biomedical Engineering and Health Care Systems
The smart system integrates cloud computing and mobile computing, also known as mobile cloud comp... more The smart system integrates cloud computing and mobile computing, also known as mobile cloud computing. This smart system helps monitor the vehicle's health condition on any device, i.e., platform-independent. Using machine learning algorithms, the smart system helps predict vehicle health and maintain the vehicle's and the driving person's safety. The cloud computing used to deploy this smart system for monitoring the vehicle condition is the Google Cloud Platform. Google Cloud Platform provides various services like Computing and Hosting, Networking, Storage, etc., which help deploy and host web applications on Google Cloud using multiple services. One of the best securities is achieved using the Google Cloud Platform. Several layers are encrypted with specially designed algorithms for the safety of the customer data and applications. Google Cloud Platform helps provide data integrity, making it better for storing all the data. It also provides Denial of Service protec...
Learning and Analytics in Intelligent Systems, 2019
Developing assistive systems for visually challenged people is an active area of research in comp... more Developing assistive systems for visually challenged people is an active area of research in computer vision community. Such system provides a medical assistive tool to take the correct medicine at the right time as prescribed by the doctor and makes visually challenged people to live independently for their day to day activities. Many prototypes were developed to deal with misidentification of medicines but are incapable of determining exact pill picked by the person. This paper presents an automated system where feature extraction is done to recognize the pills based on structural, texture and Hu moments. If the pill is picked from the medicine box, the label present on the pill is considered for Text Recognition. Pill label and expiry date are extracted from the label and classified using Convolutional Neural Network (CNN) and is converted to speech. This audio is produced to indicate the person about the medicine picked. Experimental results proved that our system is better than...
2022 International Conference on Electronics and Renewable Systems (ICEARS)
Cloud computing is one among the most crucial commercial technologies nowadays. It offers a diver... more Cloud computing is one among the most crucial commercial technologies nowadays. It offers a diverse range of services. One of the most exciting and important procedures in cloud computing is virtual machine installation (VMP). Virtual Machine Placement uses evolutionary computing to lower energy consumption while lowering the total number of physical servers that are currently in use. By examining the ant colony system’s (ACS) promising performance for combinatorial issues, Order Exchange and Ant Colony System OEMACS, an approach based on ACS finds solution by combining order exchange and migration local search strategies, was developed (Order exchange and Migration Ant Colony System). From a global optimization standpoint, The OEMACS algorithm is capable of significantly lowering the active servers in number and is used for virtual machine assignment. It also aids in the reduction of the number of active servers that are underutilized. In OEMACS, artificial ants are guided to the best feasible solution using the pheromone deposition method. It also arranges virtual machines in such a way that resource waste and power consumption are reduced. On servers with homogenous and heterogeneous VM sizes, this strategy is used. OEMACS surpasses some of the previously utilized algorithms, such as standard heuristics and other evolutionary-based techniques, according to the findings.
Now-a-days Image Processing has been the most interested subject for research. This paper present... more Now-a-days Image Processing has been the most interested subject for research. This paper presents the idea of recognizing the characters in digital image using Optical Character Recognition. The Optical Character Recognition process involves several aspects such as segmentation, feature extraction and classification. MATLAB provides a variety of functions that way providing the capabilities of developing applications and new algorithms in the field of image processing. This paper shows how to use MATLAB and its image processing toolbox functions in order to recognize characters in an image. We implement this using MATLAB for segmentation using edge detection, identification of characters, and storing the vector of characters. Optical Character Recognition (OCR) service enables application to retrieve the text that appears in a photograph. We have to first preprocess the image and image extraction as followed to find characters in a photograph. The resulting vector can be used in ma...
2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)
Rapid increase in urban settlements has caused a tremendous effect on natural deposits and habita... more Rapid increase in urban settlements has caused a tremendous effect on natural deposits and habitat. A perfect blueprint is needed for organizing the settlements without degrading the living standards. With the developed spatial technology, good quality of remote sensing data is now available. Using satellite images, change can be detected between two temporal images of the same scene. This change detection helps in the proper management of development proceedings. Exiting machine learning algorithms for change detection uses hand crafted features that may result to over-fitting problems. This paper proposes deep learning based methodology to detect the change in urban landscapes especially buildings. The proposed methodology involves a feature extractor complemented by an attention mechanism to capture the multi-scale dependencies between two pixels taken from two temporal images. With this methodology, both temporal and spatial features are taken into consideration in finding change detection.
Advances in Multimedia and Interactive Technologies
Object recognition and classification (human beings, animals, buildings, vehicles) has become imp... more Object recognition and classification (human beings, animals, buildings, vehicles) has become important in a surveillance video situated at prominent areas such as airports, banks, military installations etc., Outdoor environments are more challenging for moving object classification because of incomplete appearance details of moving objects due to occlusions and large distance between the camera and moving objects. As such, there is a need to monitor and classify the moving objects by considering the challenges of video in the real time. Training the classifiers using feature based is easier and faster than pixel-based approaches in object classification. Extraction of a set of features from the object of interest is most important for classification. Textural features, color features and structural features can be chosen for classifying the object. But in real time video, object poses are not always the same. Zernike moments have been shown to be rotation invariant and noise robus...
Optoelectronics in Machine Vision-Based Theories and Applications
Object recognition and classification has become important in a surveillance video situated at pr... more Object recognition and classification has become important in a surveillance video situated at prominent areas such as airports, banks, military installations, etc. Outdoor environments are more challenging for moving object classification because of incomplete appearance details of moving objects due to illumination changes and large distance between the camera and moving objects. As such, there is a need to monitor and classify the moving objects by considering the challenges of video in the real time. Training the classifiers using feature-based approaches is easier and faster than pixel-based approaches in object classification. Extraction of a set of features from the object of interest is most important for classification. Viewpoint and sources of light illumination plays major role in the appearance of an object. Abrupt transitions are identified using Chi-square and corners are detected using Harris corner detection. Silhouettes are captured using background subtraction and ...
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Papers by S Vasavi