loveleen Kumar - Academia.edu (original) (raw)
Papers by loveleen Kumar
EAI Endorsed Transactions on Pervasive Health and Technology
In many parts of the world, heart disease is the leading cause of mortality diagnosis is critical... more In many parts of the world, heart disease is the leading cause of mortality diagnosis is critical Towards Efficient Medical Care and prevention of heart attacks and other cardiac events. Deep learning algorithms have shown promise in accurately predicting heart disease based on medical data, including electrocardiograms (ECGs) and other health metrics. With this abstract, Specifically, we advocate for deep learning algorithm in accordance with CNNs for Deep Learning effective heart disease prediction. The proposed method uses a combination of ECG signals, demographic data, and clinical measurements Identifying risk factors for cardiovascular disease in patients. The proposed CNN-based model includes several layers, such as convolutional ones, pooling ones, and fully connected ones. The model takes input in the form of ECG signals, along with demographic data and clinical measurements, and uses convolutional layers to get features out of raw data. To lessen the effect of this, poolin...
2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), Oct 10, 2022
BioMed Research International
Prediction of gene-disease associations has grown in popularity in recent biomedical research. Ho... more Prediction of gene-disease associations has grown in popularity in recent biomedical research. However, positive and unlabeled (PU) issues and limited gene-disease association data are common concerns with present association prediction algorithms. A gene-disease association prediction approach based on Katz-enhanced inductive matrix completion is suggested in light of the abovementioned flaws. Preestimate based on the Katz technique and refined estimation based on the inductive matrix completion approach makes the model. The Katz technique is utilized to preestimate the gene-disease association on the basis of gene-disease heterogeneous network to mitigate the effects of association data-sparse and PU issues. The Katz technique, however, necessarily introduces some noise when predicting gene-disease connections due to the similarity network’s quality limitations. Therefore, the elastic net regularization approach is utilized to increase the resilience of the conventional inductive ...
International Journal of Electrical, Electronics and Computers, 2021
In the current world scenario, individuals square measure additional involved regarding their hea... more In the current world scenario, individuals square measure additional involved regarding their health. However, it's terribly troublesome to get consultation with the doctor just in case of any health problems. Since the invention of the Coronavirus (nCOV-19), it's become a world pandemic. At an equivalent time, it's been a good challenge to hospitals or health care employees to manage the flow of the high variety of cases. particularly in remote areas, it's becoming tougher to consult a doctor once the immediate hit of the epidemic has occurred. So, to steer an honest life, care is incredibly vital. The planned plan is to form a medical chatbot victimization Machine Learning algorithm which will diagnose the illness and supply basic details regarding the illness before consulting a doctor. Several studies will solve this downside with some reasonably chatbot or health assistant. This project report proposes a colloquial care larva that's designed to order, counsel and provides data on generic medicines for diseases to the patients. During this paper, we would like to explore and deepen additional information regarding chatbots that would facilitate individuals to urge an equivalent and correct treatment as a doctor would do. In addition, presenting a virtual assistant may live with the infection severity and connect with registered doctors once symptoms become serious.
Reproduced with the kind permissions of the copyright owner. Personal use of this material is per... more Reproduced with the kind permissions of the copyright owner. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ABSTRACT We discuss the design and implementation of an integrated media creation environment, and demonstrate its efficacy in the generation of two simple home movies. The significance for the average user seeking to create home movies lies in the flexible and automatic application of film principles to the task, removal of tedious low-level editing by means of wellformed media transformations in terms of high-level film constructs (e.g. tempo), and content repurposing powered by those same transformations added to the rich semantic information maintained at each phase of the process.
2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)
International Journal of Electrical, Electronics and Computers, 2021
The main objective of this work is the uniting and streamlining of an automatic face detection ap... more The main objective of this work is the uniting and streamlining of an automatic face detection application and recognition system for video indexing applications. Human identification means the classification of gender which can increase the identification accuracy. So, accurate gender classification algorithms may increase the accuracy of the applications and can reduce its complexity. But, in some applications, some challenges are there such as rotation, gray scale variations that may reduce the accuracy of the application. The main goal of building this module is to understand the values in image, pattern, and array processing with OpenCV for effective processing faces for building pipe-lining, SVM models.
International Journal of Civil, Mechanical and Energy Science, 2021
In this Pandemic phase, customers and merchants do not interact face-to-face and customers are mo... more In this Pandemic phase, customers and merchants do not interact face-to-face and customers are more discerning as a result of the additional alternatives and solutions available to them online. B2C Ecommerce provides an alleviation to this problem. Traditionally, it was the mode of commercial transaction in which companies sold items or services to customers directly. However, the term B2C is now more commonly used to refer to online product sales, often known as e-tailing, in which manufacturers or merchants sell their items to customers over the internet. This paper outlines the importance of B2C Ecommerce development in Pandemic times by shedding light on the result of the creation of B2C based online shopping website.
2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3), 2020
Machine learning techniques are widely used to take intelligent decisions in industrial and educa... more Machine learning techniques are widely used to take intelligent decisions in industrial and educational domains. In the educational domain, when a research scholar submits a dissertation, then it has to be indexed and classified. The number of dissertations that are submitted in an educational institute is usually high and if done manually, it becomes difficult to index and classify correctly. This study applies machine learning techniques to automate the indexing and categorization of dissertations. We have focused on dissertations from the Engineering, Medical, Social Science, and General Science fields. We used the Bag of Words (BoW) method to extract features and K-means, Density-based spatial clustering of applications with noise (DBSCAN) and Expectation-Maximisation (EM) to train our model. Our experimental results reveal that the proposed K- means technique for indexing and categorization leads to higher accuracy and significant reduction in negative predictions as compared t...
International Journal of Civil, Mechanical and Energy Science, 2020
Prophecy-Google Apps Analysis and Prediction" was built with an objective to help the companies t... more Prophecy-Google Apps Analysis and Prediction" was built with an objective to help the companies to identify the overall rating of their apps based on the reviews and allow the new companies to enter the market of apps with moderate/more/fewer competitors. The project is built with a user friendly interface so as to make it easy for user. The complete project inbuilt various technologies like html, CSS, machine learning, python, NLP etc. The users are also provided with other services in order to help them identify the current market demand. This web-app portal provides a platform for app owner companies to upload the file of their apps review and find out the how many reviews are positive, negative and neutral. Based on this the companies can identify the overall impression their app is making on the users. The system is built using machine learning algorithm which showed the best score among all the algorithm which makes the system highly reliable. An easy to use interface for accessing the services provides an extra advantage to the portal. Other than this it provides the current stats of the apps market, searching between the apps, navigating to the websites of most popular applications etc. all these services will help the user to understand the requirement of the market. In all it can be concluded that this portal will turn to be true friend as the name in providing the solutions.
International Journal of Recent Technology and Engineering, 2019
Face classification and recognition is the fastest growing, challenging area in real time applica... more Face classification and recognition is the fastest growing, challenging area in real time applications. A large number of algorithms are there in the network to recognize the face. It is the important part of the biometric traits and it not only contributes to the theoretical insights but also to practical insights of many algorithms. Conversely, the first face recognition in the main reckons on a priori in a row of hurdle folks and might not free itself from human intervention. Until the looks of high-speed, betterquality computers, the face recognition methodology makes a big disintegrate through. Face recognition has been a quick growing, difficult and mesmerizing space in real time applications. Facial classifications and recognition becomes an interesting research topic. A large range of face classification and recognition algorithms are developed in last decades. In this paper a attempt is created to review a good vary of strategies used for face recognition expansively. This ...
JUCS - Journal of Universal Computer Science
Image superresolution (SR) is the process of enlarging and enhancing a low-resolution image. Imag... more Image superresolution (SR) is the process of enlarging and enhancing a low-resolution image. Image superresolution helps in industrial image enhancement, classification, detection, pattern recognition, surveillance, satellite imaging, medical diagnosis, image analytics, etc. It is of utmost importance to keep the features of the low-resolution image intact while enlarging and enhancing it. In this research paper, a framework is proposed that works in three phases and generates superresolution images while keeping low-resolution image features intact and reducing image blurring and artifacts. In the first phase, image enlargement is done, which enlarges the low-resolution image to the 2x/4x scale using two standard algorithms. The second phase enhances the image using an AI-empowered Generative adversarial network (GAN). We have used a GAN with dual generators and named it EffN-GAN (EfficientNet-GAN). Fusion is done in the last phase, wherein the final improved image is generated by ...
caesjournals.org
AbstractImage segmentation plays an important role in human vision, computer vision, and pattern... more AbstractImage segmentation plays an important role in human vision, computer vision, and pattern recognition fields. Segmentation based on texture can improve the accuracy of interpretation. Satellite images are used in order to detect the distribution of classes such ...
EAI Endorsed Transactions on Pervasive Health and Technology
In many parts of the world, heart disease is the leading cause of mortality diagnosis is critical... more In many parts of the world, heart disease is the leading cause of mortality diagnosis is critical Towards Efficient Medical Care and prevention of heart attacks and other cardiac events. Deep learning algorithms have shown promise in accurately predicting heart disease based on medical data, including electrocardiograms (ECGs) and other health metrics. With this abstract, Specifically, we advocate for deep learning algorithm in accordance with CNNs for Deep Learning effective heart disease prediction. The proposed method uses a combination of ECG signals, demographic data, and clinical measurements Identifying risk factors for cardiovascular disease in patients. The proposed CNN-based model includes several layers, such as convolutional ones, pooling ones, and fully connected ones. The model takes input in the form of ECG signals, along with demographic data and clinical measurements, and uses convolutional layers to get features out of raw data. To lessen the effect of this, poolin...
2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), Oct 10, 2022
BioMed Research International
Prediction of gene-disease associations has grown in popularity in recent biomedical research. Ho... more Prediction of gene-disease associations has grown in popularity in recent biomedical research. However, positive and unlabeled (PU) issues and limited gene-disease association data are common concerns with present association prediction algorithms. A gene-disease association prediction approach based on Katz-enhanced inductive matrix completion is suggested in light of the abovementioned flaws. Preestimate based on the Katz technique and refined estimation based on the inductive matrix completion approach makes the model. The Katz technique is utilized to preestimate the gene-disease association on the basis of gene-disease heterogeneous network to mitigate the effects of association data-sparse and PU issues. The Katz technique, however, necessarily introduces some noise when predicting gene-disease connections due to the similarity network’s quality limitations. Therefore, the elastic net regularization approach is utilized to increase the resilience of the conventional inductive ...
International Journal of Electrical, Electronics and Computers, 2021
In the current world scenario, individuals square measure additional involved regarding their hea... more In the current world scenario, individuals square measure additional involved regarding their health. However, it's terribly troublesome to get consultation with the doctor just in case of any health problems. Since the invention of the Coronavirus (nCOV-19), it's become a world pandemic. At an equivalent time, it's been a good challenge to hospitals or health care employees to manage the flow of the high variety of cases. particularly in remote areas, it's becoming tougher to consult a doctor once the immediate hit of the epidemic has occurred. So, to steer an honest life, care is incredibly vital. The planned plan is to form a medical chatbot victimization Machine Learning algorithm which will diagnose the illness and supply basic details regarding the illness before consulting a doctor. Several studies will solve this downside with some reasonably chatbot or health assistant. This project report proposes a colloquial care larva that's designed to order, counsel and provides data on generic medicines for diseases to the patients. During this paper, we would like to explore and deepen additional information regarding chatbots that would facilitate individuals to urge an equivalent and correct treatment as a doctor would do. In addition, presenting a virtual assistant may live with the infection severity and connect with registered doctors once symptoms become serious.
Reproduced with the kind permissions of the copyright owner. Personal use of this material is per... more Reproduced with the kind permissions of the copyright owner. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ABSTRACT We discuss the design and implementation of an integrated media creation environment, and demonstrate its efficacy in the generation of two simple home movies. The significance for the average user seeking to create home movies lies in the flexible and automatic application of film principles to the task, removal of tedious low-level editing by means of wellformed media transformations in terms of high-level film constructs (e.g. tempo), and content repurposing powered by those same transformations added to the rich semantic information maintained at each phase of the process.
2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)
International Journal of Electrical, Electronics and Computers, 2021
The main objective of this work is the uniting and streamlining of an automatic face detection ap... more The main objective of this work is the uniting and streamlining of an automatic face detection application and recognition system for video indexing applications. Human identification means the classification of gender which can increase the identification accuracy. So, accurate gender classification algorithms may increase the accuracy of the applications and can reduce its complexity. But, in some applications, some challenges are there such as rotation, gray scale variations that may reduce the accuracy of the application. The main goal of building this module is to understand the values in image, pattern, and array processing with OpenCV for effective processing faces for building pipe-lining, SVM models.
International Journal of Civil, Mechanical and Energy Science, 2021
In this Pandemic phase, customers and merchants do not interact face-to-face and customers are mo... more In this Pandemic phase, customers and merchants do not interact face-to-face and customers are more discerning as a result of the additional alternatives and solutions available to them online. B2C Ecommerce provides an alleviation to this problem. Traditionally, it was the mode of commercial transaction in which companies sold items or services to customers directly. However, the term B2C is now more commonly used to refer to online product sales, often known as e-tailing, in which manufacturers or merchants sell their items to customers over the internet. This paper outlines the importance of B2C Ecommerce development in Pandemic times by shedding light on the result of the creation of B2C based online shopping website.
2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3), 2020
Machine learning techniques are widely used to take intelligent decisions in industrial and educa... more Machine learning techniques are widely used to take intelligent decisions in industrial and educational domains. In the educational domain, when a research scholar submits a dissertation, then it has to be indexed and classified. The number of dissertations that are submitted in an educational institute is usually high and if done manually, it becomes difficult to index and classify correctly. This study applies machine learning techniques to automate the indexing and categorization of dissertations. We have focused on dissertations from the Engineering, Medical, Social Science, and General Science fields. We used the Bag of Words (BoW) method to extract features and K-means, Density-based spatial clustering of applications with noise (DBSCAN) and Expectation-Maximisation (EM) to train our model. Our experimental results reveal that the proposed K- means technique for indexing and categorization leads to higher accuracy and significant reduction in negative predictions as compared t...
International Journal of Civil, Mechanical and Energy Science, 2020
Prophecy-Google Apps Analysis and Prediction" was built with an objective to help the companies t... more Prophecy-Google Apps Analysis and Prediction" was built with an objective to help the companies to identify the overall rating of their apps based on the reviews and allow the new companies to enter the market of apps with moderate/more/fewer competitors. The project is built with a user friendly interface so as to make it easy for user. The complete project inbuilt various technologies like html, CSS, machine learning, python, NLP etc. The users are also provided with other services in order to help them identify the current market demand. This web-app portal provides a platform for app owner companies to upload the file of their apps review and find out the how many reviews are positive, negative and neutral. Based on this the companies can identify the overall impression their app is making on the users. The system is built using machine learning algorithm which showed the best score among all the algorithm which makes the system highly reliable. An easy to use interface for accessing the services provides an extra advantage to the portal. Other than this it provides the current stats of the apps market, searching between the apps, navigating to the websites of most popular applications etc. all these services will help the user to understand the requirement of the market. In all it can be concluded that this portal will turn to be true friend as the name in providing the solutions.
International Journal of Recent Technology and Engineering, 2019
Face classification and recognition is the fastest growing, challenging area in real time applica... more Face classification and recognition is the fastest growing, challenging area in real time applications. A large number of algorithms are there in the network to recognize the face. It is the important part of the biometric traits and it not only contributes to the theoretical insights but also to practical insights of many algorithms. Conversely, the first face recognition in the main reckons on a priori in a row of hurdle folks and might not free itself from human intervention. Until the looks of high-speed, betterquality computers, the face recognition methodology makes a big disintegrate through. Face recognition has been a quick growing, difficult and mesmerizing space in real time applications. Facial classifications and recognition becomes an interesting research topic. A large range of face classification and recognition algorithms are developed in last decades. In this paper a attempt is created to review a good vary of strategies used for face recognition expansively. This ...
JUCS - Journal of Universal Computer Science
Image superresolution (SR) is the process of enlarging and enhancing a low-resolution image. Imag... more Image superresolution (SR) is the process of enlarging and enhancing a low-resolution image. Image superresolution helps in industrial image enhancement, classification, detection, pattern recognition, surveillance, satellite imaging, medical diagnosis, image analytics, etc. It is of utmost importance to keep the features of the low-resolution image intact while enlarging and enhancing it. In this research paper, a framework is proposed that works in three phases and generates superresolution images while keeping low-resolution image features intact and reducing image blurring and artifacts. In the first phase, image enlargement is done, which enlarges the low-resolution image to the 2x/4x scale using two standard algorithms. The second phase enhances the image using an AI-empowered Generative adversarial network (GAN). We have used a GAN with dual generators and named it EffN-GAN (EfficientNet-GAN). Fusion is done in the last phase, wherein the final improved image is generated by ...
caesjournals.org
AbstractImage segmentation plays an important role in human vision, computer vision, and pattern... more AbstractImage segmentation plays an important role in human vision, computer vision, and pattern recognition fields. Segmentation based on texture can improve the accuracy of interpretation. Satellite images are used in order to detect the distribution of classes such ...