Achyutha Prasad N
Biographic Data
| ID | 8419943 |
|---|---|
| NAME | Achyutha Prasad N |
| GIVEN NAMES | Achyutha N |
| FAMILY NAME | Prasad |
| SIGNATURE | N A P |
| AFFILIATIONS | ESI - Post Graduate Institute of Medical Science and Research |
| ORCID | 0000-0002-2356-4146 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 11 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Real time Covid-19 facemask detection using deep learning
The COVID-19 pandemic is producing a global health pandemic. According to the World Health Organization (WHO), the utmost effective protection is to wear a face mask in crowded regions/areas. During this pandemic, it is compulsory for every person to wear a mask and maintain social distancing. In the field of Image Processing, Convolutional Neural Networks (CNNs) have risen to prominence as the most common type of image realization/recognition mo…
Survey on NLP based automatic extractive text summarization using spacy
Automatic abstraction of text is considered one of the most difficult problems because mathematically there is no real way to test a summary but one can distinguish between the appropriate summary. Also, abbreviations may be of a variety of abstractive forms in which new phrases and terms are used, in contrast Extractive form in which scoring sentences from enter textual content gets extracted as a summary sentence. The growing discovery of onlin…
Business analysis and modelling of flight delays using artificial intelligence
In the current day, with the growth of technology the number of people travelling by flights has increased. Consistently a significant number of flights are delayed or crossed out because of numerous of reasons. These delays bother travelers. These delays also cost a lot to the aircraft organization. Flight delays negatively affect carriers, air terminals and travelers. There are different methodologies used to manufacture flight delays expectati…
Implementation of NLP based automatic text summarization using spacy
The amount of data on the Internet has increased exponentially over the past decade. Therefore, we need a solution that converts this massive amount of raw information into useful information that the human brain can understand. One such common technique in research that helps when dealing with large amounts of data is text summarization. Automatic summarization is a well-known approach to reduce documents to key ideas. This works by storing impo…
Human activity recognition using CNN and long term short term memory
Human activity recognition aims to work out the activities performed by someone in a picture or video. Examples of actions are running, sitting, sleeping, and standing. Complex movement patterns and harmful occurrences like falling may be a part of these activities. The suggested ConvLSTM network can be created by successively combining fully connected layers, long immediate memory (LSTM) networks, and convolutional neural networks (CNN). The acq…
Recognition efficiency enhancement of control chart pattern using ensemble MLP neural network
chart pattern for six different fundamental patterns have been proposed. The multilayer perceptron based neural network has applied as an entity to form the ensemble. The loss of generalization property of an individual neural network has been fulfilled by providing the diversity in the training data for the individual entity of ensemble. The outcome of individual recognizer has combined over their decision value to include the outcome knowledge …
A survey on human activity recognition using CNN and LSTM
Human Activity Recognition (HAR) plays a massive role inside the everyday life of people due to its capability to investigate tremendous high-degree data approximately human interest from wearable or stationary devices. An extensive quantity of studies has been completed on HAR and numerous techniques primarily based on deep gaining knowledge of and device analyzing were exploited through the research community to categorize human sports. The pri…
Survey on Automated Medical Image Classification Using Deep Learning
Deep Learning has indeed been widely used in many fields/areas of medicinal images classification, and a large number of publications have been published documenting its success. The key for achieving effective diagnosis and therapy is accurate characterization of medical pictures. However, because image interpretation is highly dependent on the subjective opinion of doctors, the results of image processing vary greatly amongst clinicians at diff…
A survey on blockchain security for cloud and IoT environment
In traditional Internet of Things (IoT) ecosystems, fog devices transmit data from sensors to a centralized cloud server. Issues with security and upkeep while updating firmware for millions of smart devices, single points of failure, as well as third-party Cloud server administration, the difficulty of frequently updating the firmware on millions of smart devices presents security and maintenance issues as well as a bottleneck in information flo…
Automated medical image classification using deep learning
Medical imaging is extremely important in the domain of medicine. Image classification is now utilized to distinguish aberrant tissues from healthy tissue in brain imaging. The brain tumor is identified from MRI images by using some classification techniques, where the area of the tumor as well as the tumor size is detected. Automatic tumor detection using brain MRI is efficient and time- saving, assisting the neurologists in diagnosis. Tumors ca…
Heart health prediction using web application
It is said that the “heart is health” heart acts as a valve that pumps oxygenated and deoxygenated to and from the lungs its one of the most vital organs of the body and very sensitive and vulnerable as well. It has been observed that nowadays due to changes in lifestyle, irregularities, carelessness and extensive workload are the main reason for heart attacks in many people below 40 years of age and they are prone of are getting heart attacks, a…
No prominent works on this page.
Real time Covid-19 facemask detection using deep learning
The COVID-19 pandemic is producing a global health pandemic. According to the World Health Organization (WHO), the utmost effective protection is to wear a face mask in crowded regions/areas. During this pandemic, it is compulsory for every person to wear a mask and maintain social distancing. In the field of Image Processing, Convolutional Neural Networks (CNNs) have risen to prominence as the most common type of image realization/recognition mo…
Survey on NLP based automatic extractive text summarization using spacy
Automatic abstraction of text is considered one of the most difficult problems because mathematically there is no real way to test a summary but one can distinguish between the appropriate summary. Also, abbreviations may be of a variety of abstractive forms in which new phrases and terms are used, in contrast Extractive form in which scoring sentences from enter textual content gets extracted as a summary sentence. The growing discovery of onlin…
Business analysis and modelling of flight delays using artificial intelligence
In the current day, with the growth of technology the number of people travelling by flights has increased. Consistently a significant number of flights are delayed or crossed out because of numerous of reasons. These delays bother travelers. These delays also cost a lot to the aircraft organization. Flight delays negatively affect carriers, air terminals and travelers. There are different methodologies used to manufacture flight delays expectati…
Implementation of NLP based automatic text summarization using spacy
The amount of data on the Internet has increased exponentially over the past decade. Therefore, we need a solution that converts this massive amount of raw information into useful information that the human brain can understand. One such common technique in research that helps when dealing with large amounts of data is text summarization. Automatic summarization is a well-known approach to reduce documents to key ideas. This works by storing impo…
Human activity recognition using CNN and long term short term memory
Human activity recognition aims to work out the activities performed by someone in a picture or video. Examples of actions are running, sitting, sleeping, and standing. Complex movement patterns and harmful occurrences like falling may be a part of these activities. The suggested ConvLSTM network can be created by successively combining fully connected layers, long immediate memory (LSTM) networks, and convolutional neural networks (CNN). The acq…
Recognition efficiency enhancement of control chart pattern using ensemble MLP neural network
chart pattern for six different fundamental patterns have been proposed. The multilayer perceptron based neural network has applied as an entity to form the ensemble. The loss of generalization property of an individual neural network has been fulfilled by providing the diversity in the training data for the individual entity of ensemble. The outcome of individual recognizer has combined over their decision value to include the outcome knowledge …
A survey on human activity recognition using CNN and LSTM
Human Activity Recognition (HAR) plays a massive role inside the everyday life of people due to its capability to investigate tremendous high-degree data approximately human interest from wearable or stationary devices. An extensive quantity of studies has been completed on HAR and numerous techniques primarily based on deep gaining knowledge of and device analyzing were exploited through the research community to categorize human sports. The pri…
Survey on Automated Medical Image Classification Using Deep Learning
Deep Learning has indeed been widely used in many fields/areas of medicinal images classification, and a large number of publications have been published documenting its success. The key for achieving effective diagnosis and therapy is accurate characterization of medical pictures. However, because image interpretation is highly dependent on the subjective opinion of doctors, the results of image processing vary greatly amongst clinicians at diff…
A survey on blockchain security for cloud and IoT environment
In traditional Internet of Things (IoT) ecosystems, fog devices transmit data from sensors to a centralized cloud server. Issues with security and upkeep while updating firmware for millions of smart devices, single points of failure, as well as third-party Cloud server administration, the difficulty of frequently updating the firmware on millions of smart devices presents security and maintenance issues as well as a bottleneck in information flo…
Automated medical image classification using deep learning
Medical imaging is extremely important in the domain of medicine. Image classification is now utilized to distinguish aberrant tissues from healthy tissue in brain imaging. The brain tumor is identified from MRI images by using some classification techniques, where the area of the tumor as well as the tumor size is detected. Automatic tumor detection using brain MRI is efficient and time- saving, assisting the neurologists in diagnosis. Tumors ca…
Heart health prediction using web application
It is said that the “heart is health” heart acts as a valve that pumps oxygenated and deoxygenated to and from the lungs its one of the most vital organs of the body and very sensitive and vulnerable as well. It has been observed that nowadays due to changes in lifestyle, irregularities, carelessness and extensive workload are the main reason for heart attacks in many people below 40 years of age and they are prone of are getting heart attacks, a…
Computer Science (11 works) · Artificial Intelligence (8 works) · Pattern recognition (psychology (5 works) · Computer vision (3 works) · Convolutional neural network (3 works) · Deep learning (3 works) · Machine learning (3 works) · Mathematics (3 works) · Abstraction (2 works) · Advanced Text Analysis Techniques (2 works)