Papers by Dr SUVARNA NANDYAL
International Journal for Research in Applied Science and Engineering Technology
Technological advancement, including machine learning, has a significant impact on health by allo... more Technological advancement, including machine learning, has a significant impact on health by allowing for more accurate diagnosis and treatment of various chronic diseases. Accurate prediction is critical in the biomedical and healthcare communities for determining the risk of disease in patients. The only way to overcome chronic disease mortality is to predict it earlier so that disease prevention can be implemented. Such a model is a Patient's requirement for which Machine Learning is highly recommended. However, a doctor finds it difficult to make an exact forecast based just on symptoms. The most challenging task is making an accurate diagnosis of a disease. Data mining is crucial in helping to predict the sickness and solve this issue. Based on a dataset for chronic diseases from the UCI machine learning data warehouse, this study assesses chronic diseases using machine learning techniques. In order to create accurate prediction models for various chronic diseases using data mining approaches, we employ datasets for heart disease, kidney disease, cancer disease, and diabetes disease. To increase accuracy and shorten training time, the dataset's most pertinent features are chosen. The system evaluates the user's symptoms as input and outputs the likelihood that the disease will occur. The implementation of Logistic Regression is used to predict disease. Prediction of diseases like diabetes, heart disease, cancer, and kidney disease using logistic regression, random forest, and decision trees are performed. Different models, methodologies, and algorithms are utilized to forecast and analyses each chronic disease. The study includes a conceptual model that includes the prediction of the majority of chronic diseases.
2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)
Algorithms for intelligent systems, 2022
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
International Journal of Advanced Computer Science and Applications
The advancement of hardware and deep learning technologies has made it possible to apply these te... more The advancement of hardware and deep learning technologies has made it possible to apply these technologies to a variety of fields. A deep learning architecture, the Convolutional Neural Network (CNN), revolutionized the field of computer vision. One of the most popular applications of computer vision is in sports. There are different types of events in cricket, which makes it a complex game. This task introduces a new dataset called SNWOLF for detecting Umpire postures and categorizing events in cricket match. The proposed dataset will be a preliminary help, it was assessed in system development for the automatic generation of highlights from cricket sport. When it comes to cricket, the umpire has the authority to make crucial decisions about on-field incidents. The referee signals important incidents with hand signals and gestures that are one-of-a-kind. Based on detecting the referee's stance from the cricket video referee action frame, it identifies most frequently used events classification: SIX, NO BALL, WIDE, OUT, LEG BYE, and FOUR. The proposed method utilizes Convolutional Neural Networks (CNNs) architecture to extract features and classify identified frames into Umpire postures of six event classes. Here created a completely new dataset of 1040 images of Umpire Action Images containing these six events. Our method train CNNs classifier on 80% images of SNWOLF dataset and tested on 20% of remaining images. Our approach achieves an average overall accuracy of 98.20% and converges on very low crossentropy losses. The proposed system is a influential answer for generation of cricket sport highlights.
International Journal of Innovative Technology and Exploring Engineering, 2019
The modern era of digital devices which will be equipped with the dedicated machine will have the... more The modern era of digital devices which will be equipped with the dedicated machine will have the built in features to perform the special needs of the human. The mobile devices comes with the special cameras which will produces the high quality images. Human face and the facial expression system has been in the interesting field due to the great level of application it possesses. The face unlock, face detection in security areas and also the facial expression recognition has been in demand of development. The human exhibits the multiple type of expressions anger, sad, surprise, happy and many more. These expressions have special notation based on the human feelings and scenario. The Digital image processing technology has provided the tools to work with the images and will use the edge features, skin mapping and supervised knowledge based classifier to recognize the expressions posed by the human to assist the need.
Lecture notes in electrical engineering, 2022
2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)
International Journal of Computer Applications, 2017
Journal of Physics: Conference Series, 2021
Gesture Recognition pertains to recognizing meaningful expressions of motion by a human, involvin... more Gesture Recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost importance in designing an intelligent and efficient human–computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation, monitoring patients or elder people, surveillance systems, sports gesture analysis, human behaviour analysis etc., to virtual reality. In recent years, there has been increased interest in video summarization and automatic sports highlights generation in the game of Cricket. In Cricket, the Umpire has the authority to make important decisions about events on the field. The Umpire signals important events using unique hand on signals and gestures. The primary intention of our work is to design and develop a new robust method for Umpire Action and Non-Action Gesture Identification and Recognition based on the Umpire Segmentation and the propo...
INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH
H.264/AVC standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts... more H.264/AVC standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The H.264/AVC standardization is now achieving signicant improvement in rate-distortion efciency for digital systems worldwide. This paper provides an overview of the technical features of H.264/AVC, describing its baseline proles, motion estimation for inter, and intra prediction. To improve the human perceptual quality of videos deblocking lter and perceptual quality assessments are described in detail.
A novel technique for the recognition of occasions in cricket recordings utilizing Umpire hand fl... more A novel technique for the recognition of occasions in cricket recordings utilizing Umpire hand flags or motions is proposed. Critical occasions in the amusement are motioned by Umpire with one of kind signals. Scene division of cricket video is at first completed by the discovery of playing occasions. At that point the Umpire edges are recognized from every scene and dissected utilizing both vertical and even power projection profiles. These profiles speaking to the Umpire signals in the casing, can be utilized as components for preparing a gathering classifier Random Backwoods (RF) for the extraction of occasions FOUR, SIX, NO BALL, OUT and WIDE in cricket diversion. The technique is tried with recorded video of some universal Twenty-Twenty cricket matches and found that occasion distinguishing proof utilizing Umpire motions matches with physically identified occasions.
2021 6th International Conference for Convergence in Technology (I2CT)
The identification of most important frames in games videos is a universal issue for several purp... more The identification of most important frames in games videos is a universal issue for several purposes, such as games categorization, recognition of acts, Human identification, object classification and video summarization. These tasks can be carried out greater efficaciously as an alternative to maintaining the entire recording, only a handful of main frames are used. In an immense corpus of preparing information to show the models, existing key casing discovery strategies is commonly anticipated managed examination and include manual stamping of keyframes. Naming requires human marginalize from various foundations to clarify key casings in recordings which aren't just costly and tedious yet additionally inclined to emotional blunders and irregularities between the labelers. To beat these problems, we propose a programmed self-managed strategy for distinguishing key casings in a video. To beat these issues, we suggest programmed and self-directed division and examination of Umpire keyframe of side interest in cricket video photographs by means of filtering Blur, Sky oriented, Replay, and Crowded frames which are now not useful frames for the Umpire Action Recognition in Highlight Extraction. Our method comprises an algorithm which segments umpire Key Frames by filtering Blur, Crowded, Replay and Sky view oriented frames for the manually selected ODI Cricket Video of Length 2:12:38 seconds. The projected scheme works in two parts. In 1st part HOG features are calculated for filtering images to train the SVM model. In second part trained SVM test the remaining test video frames based on knowledge base to filter the unnecessary images of Cricket Video. Our classifier displays radiant outcomes with right non-informative Video Frames identification and arrangement have demonstrated diminished Frames of cricket video with decreased handling time.
International Journal of Science and Applied Information Technology
A slew of motion detection methods have been proposed in recent years. The background includes so... more A slew of motion detection methods have been proposed in recent years. The background includes some constraints such as changes in illumination, shadow, cluttered the background, scene change and speed of dance between hand gestures and body gestures are different. One of the most basic methods for background subtraction is temporal averaging. We looked at a new adaptive temporal averaging approach in this paper. To identify moving objects in video sequences, an adaptive temporal averaging technique is used. Depending upon the speed of the technique we proposed a Gaussian distribution technique. Gaussian distribution done background subtraction depending upon active pixels it differentiates whether it is a background or foreground. The background model's update rate has been modified to be adaptive and determined by pixel difference .Our aim is to improve the method's F-measure by making it more adaptable to various scene scenarios. The experiment results are shown and evalu...
Scalable Comput. Pract. Exp., 2020
One of the most-watched and a played sport is cricket, especially in South Asian countries. In cr... more One of the most-watched and a played sport is cricket, especially in South Asian countries. In cricket, the umpire has the power to make significant decisions about events in the field. With the growing increase in the utilization of technology in sports, this paper presents the umpire detection and classification by proposing an optimization algorithm. The overall procedure of the proposed approach involves three steps, like segmentation, feature extraction, and classification. At first, the video frames are extracted from the input cricket video, and the segmentation is performed based on the Viola-Jones algorithm. Once the segmentation is done, the feature extraction is carried out using Histogram of Oriented Gradients (HOG), and Fuzzy Local Gradient Patterns (Fuzzy LGP). Finally, the extracted features are given to the classification step. Here, the classification is done using the proposed Bird Swarm Optimization-based stacked autoencoder deep learning classifier (BSO-Stacked A...
2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT), 2018
Prisoners are very dangerous and it’s very difficult for the police department to monitor them be... more Prisoners are very dangerous and it’s very difficult for the police department to monitor them because, there are chances that the prisoners can try to escape from the prison. To overcome this problem, the present work has been proposed. The work deals with design and development of an automated system to analyze the posture and behavior of the prisoners using the sensors namely, accelerometer sensors and smoke sensor. The sensors are placed on the body of the prisoner mainly, arm, leg and back part. The sensor values will be uploaded on to the cloud periodically. Whenever, the prisoner makes a movement to escape or any misbehavior activities are found, the updated sensor values alert the admin that the prisoner is trying to escape.
2021 6th International Conference for Convergence in Technology (I2CT), 2021
The identification of most important frames in games videos is a universal issue for several purp... more The identification of most important frames in games videos is a universal issue for several purposes, such as games categorization, recognition of acts, Human identification, object classification and video summarization. These tasks can be carried out greater efficaciously as an alternative to maintaining the entire recording, only a handful of main frames are used. In an immense corpus of preparing information to show the models, existing key casing discovery strategies is commonly anticipated managed examination and include manual stamping of keyframes. Naming requires human marginalize from various foundations to clarify key casings in recordings which aren't just costly and tedious yet additionally inclined to emotional blunders and irregularities between the labelers. To beat these problems, we propose a programmed self-managed strategy for distinguishing key casings in a video. To beat these issues, we suggest programmed and self-directed division and examination of Umpi...
Intelligent Data Communication Technologies and Internet of Things
The hand gesture technique that is regarded as the natural and easy method for the human-machine ... more The hand gesture technique that is regarded as the natural and easy method for the human-machine interaction, has paved way for the development of the multitudes of applications. The hand gestures basically employed in most of the application are either sensor based or the vision based. In case of verbal communication the gesture depiction involves the application of the natural and the bare hand gestures. So the paper proposes a bare hand gesture recognition with the light in variance conditions, involving the image cropping algorithm in the preprocessing, considering only the region of interest. The mapping of the image oriented histogram is primarily done utilizing the Euclidean distance method and further supervised neural network are trained using the images mapped, to have a better recognition of images with the same gestures under different light intensities.
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Papers by Dr SUVARNA NANDYAL