sai kopparthi | University of California, Davis (original) (raw)
Papers by sai kopparthi
International Journal of Innovative Technology and Exploring Engineering, 2020
The topic of Human activity recognition (HAR) is a prominent research area topic in the field of ... more The topic of Human activity recognition (HAR) is a prominent research area topic in the field of computer vision and image processing area. It has empowered state-of-art application in multiple sectors, surveillance, digital entertainment and medical healthcare. It is interesting to observe and intriguing to predict such kind of movements. Several sensor-based approaches have also been introduced to study and predict human activities such accelerometer, gyroscope, etc., it has its own advantages and disadvantages.[10] In this paper, an intelligent human activity recognition system is developed. Convolutional neural network (CNN) with spatiotemporal three dimensional (3D) kernels are trained using Kinetics data set which has 400 classes that depicts activities of humans in their everyday life and work and consist of 400 and more videos for each class. The 3D CNN model used in this model is RESNET-34. The videos were temporally cut down and last around tenth of a second. The trained m...
Programming comments in the form of Javadoc, docstrings orinlinecommentsarekeytotheunderstanding... more Programming comments in the form of Javadoc, docstrings
orinlinecommentsarekeytotheunderstandingsourcecode.Thepracticeofaddingcommentstosourcecodeshasevolved
due to the need to be able to understand the source code by
the developer himself and others who are trying to reuse the
code. Its natural to have varied styles of writing commentsunless it is guided by a set of specications or rules from a
programming language community. An example of how the
comments in Java programs should be documented is themanifestation of Javadocs. A Javadoc comment is writtenin HTML and must precede a class, eld, constructor or
methoddeclaration.Itismadeupoftwoparts–adescription
followed by block tags. In this example, the block tags are
@param, @return
—In the evaluation of software for exploitable vulner-abilities and other faults, automated testi... more —In the evaluation of software for exploitable vulner-abilities and other faults, automated testing is heavily utilized. One automated testing technique that has been proven effective is fuzz testing, or fuzzing, a technique which provides inputs to a program under test in order to exercise and test different parts of the program and attempt to induce undefined or undesired behavior. In this survey, we separate fuzzing techniques into three approaches: black box, white box, and grey box. For each of these approaches, we describe the motivation for utilizing the particular approach, the applicability of the approach in the context of fuzzable programs, and describe up-to-date techniques which fall under each approach. Additionally, at least one technique surveyed in each approach incorporates machine learning, so these use cases are described as well.
Book Reviews by sai kopparthi
The dataset is taken from UCI Repository named as Heterogeneity Activity Recognition DataSet. The... more The dataset is taken from UCI Repository named as Heterogeneity Activity Recognition DataSet. The data is characterized as Multivariate and is used for an associated task like Clustering and classification.
The dataset contains the readings of two motion sensors commonly found in smart-phones. Reading were recorded while users executed activities scripted in no specific order carrying smartwatches and smartphones.
We need to recognize the human activities of the different user by using Classification and clustering techniques.
International Journal of Innovative Technology and Exploring Engineering, 2020
The topic of Human activity recognition (HAR) is a prominent research area topic in the field of ... more The topic of Human activity recognition (HAR) is a prominent research area topic in the field of computer vision and image processing area. It has empowered state-of-art application in multiple sectors, surveillance, digital entertainment and medical healthcare. It is interesting to observe and intriguing to predict such kind of movements. Several sensor-based approaches have also been introduced to study and predict human activities such accelerometer, gyroscope, etc., it has its own advantages and disadvantages.[10] In this paper, an intelligent human activity recognition system is developed. Convolutional neural network (CNN) with spatiotemporal three dimensional (3D) kernels are trained using Kinetics data set which has 400 classes that depicts activities of humans in their everyday life and work and consist of 400 and more videos for each class. The 3D CNN model used in this model is RESNET-34. The videos were temporally cut down and last around tenth of a second. The trained m...
Programming comments in the form of Javadoc, docstrings orinlinecommentsarekeytotheunderstanding... more Programming comments in the form of Javadoc, docstrings
orinlinecommentsarekeytotheunderstandingsourcecode.Thepracticeofaddingcommentstosourcecodeshasevolved
due to the need to be able to understand the source code by
the developer himself and others who are trying to reuse the
code. Its natural to have varied styles of writing commentsunless it is guided by a set of specications or rules from a
programming language community. An example of how the
comments in Java programs should be documented is themanifestation of Javadocs. A Javadoc comment is writtenin HTML and must precede a class, eld, constructor or
methoddeclaration.Itismadeupoftwoparts–adescription
followed by block tags. In this example, the block tags are
@param, @return
—In the evaluation of software for exploitable vulner-abilities and other faults, automated testi... more —In the evaluation of software for exploitable vulner-abilities and other faults, automated testing is heavily utilized. One automated testing technique that has been proven effective is fuzz testing, or fuzzing, a technique which provides inputs to a program under test in order to exercise and test different parts of the program and attempt to induce undefined or undesired behavior. In this survey, we separate fuzzing techniques into three approaches: black box, white box, and grey box. For each of these approaches, we describe the motivation for utilizing the particular approach, the applicability of the approach in the context of fuzzable programs, and describe up-to-date techniques which fall under each approach. Additionally, at least one technique surveyed in each approach incorporates machine learning, so these use cases are described as well.
The dataset is taken from UCI Repository named as Heterogeneity Activity Recognition DataSet. The... more The dataset is taken from UCI Repository named as Heterogeneity Activity Recognition DataSet. The data is characterized as Multivariate and is used for an associated task like Clustering and classification.
The dataset contains the readings of two motion sensors commonly found in smart-phones. Reading were recorded while users executed activities scripted in no specific order carrying smartwatches and smartphones.
We need to recognize the human activities of the different user by using Classification and clustering techniques.