Vijay Rajpurohit | Gogte Institute of Technology (original) (raw)
Papers by Vijay Rajpurohit
2019 1st International Conference on Advances in Information Technology (ICAIT), 2019
Chat-Bot system is a part of natural language processing, where it requires system to be trained ... more Chat-Bot system is a part of natural language processing, where it requires system to be trained as per the human language, so that it can satisfy the needs of the user. Agriculture domain is leading source of countries growth. At present farmers are not much aware about recent technologies and practices being used in agriculture field. Extraction of meaningful answer by machine learning techniques is a problem, that has been studied by many machine learning experts as well as advanced machine learning techniques are introduced. These techniques are applied to extract the accurate answer. We can call this as an Agriculture Question Answering System, where the farmer can query the system and the system understands the query and responds to a given query. In this paper, we have reviewed extracting a precise answer for a given question by mainly focusing on machine learning techniques. We have made suggestions and provided the comparative analysis.
2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2020
Feature extraction is one of the important steps in image processing because the accuracy of the ... more Feature extraction is one of the important steps in image processing because the accuracy of the system would completely depend on this step. Human soft tissues are diagnosed by a diverse set of image scanning techniques namely Sonographer, Tomography and Magnetic resonance imaging (MRI). All these Imaging techniques are applied depending on the nature of the disease and type of organ. Texture analysis of the liver can be used for classifying the liver into normal and diseased. The texture is a fusion of repeated patterns that have regular or irregular frequency [5]. Texture visualization feature helps in the classification of the disease. Different textural analysis techniques have been developed for extracting texture features of the liver for classification such as structure base, statistical-based, model-based, transform-based and further classification is done by using single classifier or combination of classifiers. Here, the Microscopic images of the liver are used to classify it into the normal liver and diseased liver. The texture features are extracted using the 1st order and 2nd order feature extraction techniques. The texture analysis helps in classifying the liver cancer into benign or malignant.
International Journal of Knowledge-based and Intelligent Engineering Systems, 2021
Over the last few decades, multiple advances have been done for the classification of vegetation ... more Over the last few decades, multiple advances have been done for the classification of vegetation area through land cover, and land use. However, classification problem is one of the most complicated and contradicting problems that has received considerable attention. Therefore, to tackle this problem, this paper proposes a new Firefly-Harmony search based Deep Belief Neural Network method (FHS-DBN) for the classification of land cover, and land use. The segmentation process is done using Bayesian Fuzzy Clustering,and the feature matrix is developed. The feature matrix is given to the proposed FHS-DBN method that distinguishes the land coverfrom the land use in the multispectral satellite images, for analyzing the vegetation area. The proposed FHS-DBN method is designedby training the DBN using the FHS algorithm, which is developed by the combination of Firefly Algorithm (FA) and Harmony Search (HS) algorithm. The performance of the FHS-DBN model is evaluated using three metrics, suc...
International Journal of Computer Vision and Image Processing, 2021
MRI technique is widely used in the field of medicine because of its high spatial resolution, non... more MRI technique is widely used in the field of medicine because of its high spatial resolution, non-invasive characteristics, and soft tissue contrast. In this review article, a systematic study has been conducted to analyze the performance and issues of various techniques for brain tumor segmentation. Latest research on BTS in MRI with the higher resolution is utilized for the systematic review. The high-resolution images increase execution time of the classification, and accuracy is the other problem in BTS. Still, there is some research lacking in accuracy on the brain segmentation. Few researchers carried out the classification of different kinds of tissues in the brain images and also on the prediction on growth of tumor. Each method has specific technique to improve the performance of the BTS, and these methods are compared with one another in terms of result. Research comparison helps to understand the proposed method with their achieved results. Clustering algorithms such as K...
2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS), 2018
The primary objective of sentiment analysis system is to automatically discover and analyze peopl... more The primary objective of sentiment analysis system is to automatically discover and analyze people’s attitude, opinion, or position towards a product, a topic, a person or an entity. A huge amount of multimedia content is being posted on social websites such as YouTube, Flicker, and Twitter on every day. To cope up with such multimedia data, there is a need for state-of-the-art multimodal sentiment analysis framework that can extract information from multimodal data. The purpose of this research work is to improve the accuracy of sentiment prediction by analyzing the textual features along with facial expressions. We examine what people say and their facial expressions when they are saying it. Bag-of-words representation is used to create textual features. Facial expressions and audio features were extracted using open source tools such as OpenFace and OpenSmile respectively. Unimodal, bimodal, trimodal and ensemble approaches were used for classification. Our results demonstrate proposed ensemble approach outperforms other base models.
2019 IEEE 5th International Conference for Convergence in Technology (I2CT), 2019
As we know that data captured from various agricultural sensors is in the infinite sequence. This... more As we know that data captured from various agricultural sensors is in the infinite sequence. This data can also be called as Agricultural Unstructured data. It is necessary to find out the useful information from the big volume of unstructured data for scientific analysis, predictions to improve agricultural productivity. In the preceding paper we are providing a framework which can solve the problem of randomly stored big data volume. This paper basically deals with classification of agricultural sensor generated data by distinguishing the classes according to sources as sensors such as soil moisture sensor, soil temperature sensor, heat sensor and so on. Each sensor produces variety of data which can be classified by using the proposed Pro-Brokering algorithm.
This paper deals with parallel implementation of depth map generation for stereo images with clus... more This paper deals with parallel implementation of depth map generation for stereo images with cluster computing setup. The well-known area based Single Matching Phase stereo algorithm (SMP), whose performance is better as compared to traditional stereo matching algorithms is considered for parallel implementation. Low cost web cameras are used for construction of stereo rig and Beowulf cluster architecture, which performs near to supercomputing performance, is for parallel stereo image processing. The depth map generated can be used for object detection and Robot path planning.
Now a days, the classification and grading is performed based on observations and through experie... more Now a days, the classification and grading is performed based on observations and through experience. The system utilizes image-processing techniques to classify and grade fruits. The developed system starts the process by capturing the fruit's image using a regular digital camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. The fruits are classified based on color and graded based on size. Both classification and grading are realized by Fuzzy Logic approach. The results obtained are very promising.
International Journal of Interactive Multimedia and Artificial Intelligence, 2020
The availability of an enormous quantity of multimodal data and its widespread applications, auto... more The availability of an enormous quantity of multimodal data and its widespread applications, automatic sentiment analysis and emotion classification in the conversation has become an interesting research topic among the research community. The interlocutor state, context state between the neighboring utterances and multimodal fusion play an important role in multimodal sentiment analysis and emotion detection in conversation. In this article, the recurrent neural network (RNN) based method is developed to capture the interlocutor state and contextual state between the utterances. The pair-wise attention mechanism is used to understand the relationship between the modalities and their importance before fusion. First, two-two combinations of modalities are fused at a time and finally, all the modalities are fused to form the trimodal representation feature vector. The experiments are conducted on three standard datasets such as IEMOCAP, CMU-MOSEI, and CMU-MOSI. The proposed model is evaluated using two metrics such as accuracy and F1-Score and the results demonstrate that the proposed model performs better than the standard baselines.
The Computer Journal, 2020
Super-resolution offers a new image with high resolution from the low-resolution (LR) image that ... more Super-resolution offers a new image with high resolution from the low-resolution (LR) image that is highly employed for the numerous remote sensing applications. Most of the existing techniques for formation of the super-resolution image exhibit the loss of quality and deviation from the original multi-spectral LR image. Thus, this paper aims at proposing an efficient super-resolution method using the hybrid model. The hybrid model is developed using the support vector regression model and multi-support vector neural network (MSVNN), and the weights of the MSVNN is tuned optimally using the proposed algorithm. The proposed DolLion algorithm is the integration of the dolphin echolocation algorithm and lion optimization algorithm that exhibits better convergence and offers a global optimal solution. The experimentation is performed using the datasets taken from the multi-spectral scene images. The optimal and effective formation of the super-resolution image using the proposed hybrid ...
International Journal of Engineering and Advanced Technology, 2020
Data visualization is the technique for analyzing the data from the collected dataset. Different ... more Data visualization is the technique for analyzing the data from the collected dataset. Different plots can be drawn for the data visualization. Microscopic images of the liver are being collected as a dataset from the authorized laboratory and the Joint plot, Violin plot and distribution plot are applied on them for the analysis which helps to extract the specific features and for the classification. Joint plot uses the scatter plot and Histogram technique in order to visualize the data. Violin plot technique is used for plotting the numeric data which helps in gray level co-occurrence matrix. Distribution graph is plotted to check the distribution of tones captured in the image so that we can differentiate based on the tones. All three graphs plotted extract the different features which help in efficient analysis.
International Journal of Intelligent Engineering Informatics, 2020
Multimodal affective computing has become a popular research area, due to the availability of a l... more Multimodal affective computing has become a popular research area, due to the availability of a large amount of multimodal content. Feature alignment between the modalities and multimodal fusion are the most important issues in multimodal affective computing. To address these issues, the proposed model extracts the features at word-level and forced alignment is used to understand the time-dependent interaction among the modalities. The contextual information among the words of an utterance and between the nearby utterances is extracted using bidirectional long short term memory (LSTM). Weighted pooling based attention model is used to select the important features within the modalities and importance of each modality. Information from multiple modalities is fused using a cross-modality fusion technique. The performance of the proposed model was tested on two standard datasets such as IEMOCAP and CMU-MOSI. By incorporating the word-level features, feature alignment, and cross-modality fusion, the proposed architecture outperforms the baselines in terms of classification accuracy.
International Journal of Computer Applications, 2019
International Journal of Computer Sciences and Engineering, 2019
International Journal of Fruit Science, 2018
Grading and quality assessment is an important aspect of postharvest management in pomegranate fr... more Grading and quality assessment is an important aspect of postharvest management in pomegranate fruits. In India, the quality assessment is usually performed manually by feeling the fruit in hand. This manual assessment poses a lot of disadvantages such as uncertainty, tediousness, time consumption etc. Moreover there are no well-organized grading systems for testing quality of pomegranates. Aim of the present research work is to eliminate such problems associated with manual quality assessment by incorporating Machine Intelligence and Digital Image Processing techniques. The present work precisely redefines the new quality parameters associated with the existing grading criteria. The research work also proposes a unique Effective Quality Assessment (EQA) algorithm comprising of a holistic approach towards the grading and quality assessment of pomegranate fruits. Results of the research work are found to be 97.83% by using Artificial Neural Networks.
2019 1st International Conference on Advances in Information Technology (ICAIT), 2019
Chat-Bot system is a part of natural language processing, where it requires system to be trained ... more Chat-Bot system is a part of natural language processing, where it requires system to be trained as per the human language, so that it can satisfy the needs of the user. Agriculture domain is leading source of countries growth. At present farmers are not much aware about recent technologies and practices being used in agriculture field. Extraction of meaningful answer by machine learning techniques is a problem, that has been studied by many machine learning experts as well as advanced machine learning techniques are introduced. These techniques are applied to extract the accurate answer. We can call this as an Agriculture Question Answering System, where the farmer can query the system and the system understands the query and responds to a given query. In this paper, we have reviewed extracting a precise answer for a given question by mainly focusing on machine learning techniques. We have made suggestions and provided the comparative analysis.
2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2020
Feature extraction is one of the important steps in image processing because the accuracy of the ... more Feature extraction is one of the important steps in image processing because the accuracy of the system would completely depend on this step. Human soft tissues are diagnosed by a diverse set of image scanning techniques namely Sonographer, Tomography and Magnetic resonance imaging (MRI). All these Imaging techniques are applied depending on the nature of the disease and type of organ. Texture analysis of the liver can be used for classifying the liver into normal and diseased. The texture is a fusion of repeated patterns that have regular or irregular frequency [5]. Texture visualization feature helps in the classification of the disease. Different textural analysis techniques have been developed for extracting texture features of the liver for classification such as structure base, statistical-based, model-based, transform-based and further classification is done by using single classifier or combination of classifiers. Here, the Microscopic images of the liver are used to classify it into the normal liver and diseased liver. The texture features are extracted using the 1st order and 2nd order feature extraction techniques. The texture analysis helps in classifying the liver cancer into benign or malignant.
International Journal of Knowledge-based and Intelligent Engineering Systems, 2021
Over the last few decades, multiple advances have been done for the classification of vegetation ... more Over the last few decades, multiple advances have been done for the classification of vegetation area through land cover, and land use. However, classification problem is one of the most complicated and contradicting problems that has received considerable attention. Therefore, to tackle this problem, this paper proposes a new Firefly-Harmony search based Deep Belief Neural Network method (FHS-DBN) for the classification of land cover, and land use. The segmentation process is done using Bayesian Fuzzy Clustering,and the feature matrix is developed. The feature matrix is given to the proposed FHS-DBN method that distinguishes the land coverfrom the land use in the multispectral satellite images, for analyzing the vegetation area. The proposed FHS-DBN method is designedby training the DBN using the FHS algorithm, which is developed by the combination of Firefly Algorithm (FA) and Harmony Search (HS) algorithm. The performance of the FHS-DBN model is evaluated using three metrics, suc...
International Journal of Computer Vision and Image Processing, 2021
MRI technique is widely used in the field of medicine because of its high spatial resolution, non... more MRI technique is widely used in the field of medicine because of its high spatial resolution, non-invasive characteristics, and soft tissue contrast. In this review article, a systematic study has been conducted to analyze the performance and issues of various techniques for brain tumor segmentation. Latest research on BTS in MRI with the higher resolution is utilized for the systematic review. The high-resolution images increase execution time of the classification, and accuracy is the other problem in BTS. Still, there is some research lacking in accuracy on the brain segmentation. Few researchers carried out the classification of different kinds of tissues in the brain images and also on the prediction on growth of tumor. Each method has specific technique to improve the performance of the BTS, and these methods are compared with one another in terms of result. Research comparison helps to understand the proposed method with their achieved results. Clustering algorithms such as K...
2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS), 2018
The primary objective of sentiment analysis system is to automatically discover and analyze peopl... more The primary objective of sentiment analysis system is to automatically discover and analyze people’s attitude, opinion, or position towards a product, a topic, a person or an entity. A huge amount of multimedia content is being posted on social websites such as YouTube, Flicker, and Twitter on every day. To cope up with such multimedia data, there is a need for state-of-the-art multimodal sentiment analysis framework that can extract information from multimodal data. The purpose of this research work is to improve the accuracy of sentiment prediction by analyzing the textual features along with facial expressions. We examine what people say and their facial expressions when they are saying it. Bag-of-words representation is used to create textual features. Facial expressions and audio features were extracted using open source tools such as OpenFace and OpenSmile respectively. Unimodal, bimodal, trimodal and ensemble approaches were used for classification. Our results demonstrate proposed ensemble approach outperforms other base models.
2019 IEEE 5th International Conference for Convergence in Technology (I2CT), 2019
As we know that data captured from various agricultural sensors is in the infinite sequence. This... more As we know that data captured from various agricultural sensors is in the infinite sequence. This data can also be called as Agricultural Unstructured data. It is necessary to find out the useful information from the big volume of unstructured data for scientific analysis, predictions to improve agricultural productivity. In the preceding paper we are providing a framework which can solve the problem of randomly stored big data volume. This paper basically deals with classification of agricultural sensor generated data by distinguishing the classes according to sources as sensors such as soil moisture sensor, soil temperature sensor, heat sensor and so on. Each sensor produces variety of data which can be classified by using the proposed Pro-Brokering algorithm.
This paper deals with parallel implementation of depth map generation for stereo images with clus... more This paper deals with parallel implementation of depth map generation for stereo images with cluster computing setup. The well-known area based Single Matching Phase stereo algorithm (SMP), whose performance is better as compared to traditional stereo matching algorithms is considered for parallel implementation. Low cost web cameras are used for construction of stereo rig and Beowulf cluster architecture, which performs near to supercomputing performance, is for parallel stereo image processing. The depth map generated can be used for object detection and Robot path planning.
Now a days, the classification and grading is performed based on observations and through experie... more Now a days, the classification and grading is performed based on observations and through experience. The system utilizes image-processing techniques to classify and grade fruits. The developed system starts the process by capturing the fruit's image using a regular digital camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. The fruits are classified based on color and graded based on size. Both classification and grading are realized by Fuzzy Logic approach. The results obtained are very promising.
International Journal of Interactive Multimedia and Artificial Intelligence, 2020
The availability of an enormous quantity of multimodal data and its widespread applications, auto... more The availability of an enormous quantity of multimodal data and its widespread applications, automatic sentiment analysis and emotion classification in the conversation has become an interesting research topic among the research community. The interlocutor state, context state between the neighboring utterances and multimodal fusion play an important role in multimodal sentiment analysis and emotion detection in conversation. In this article, the recurrent neural network (RNN) based method is developed to capture the interlocutor state and contextual state between the utterances. The pair-wise attention mechanism is used to understand the relationship between the modalities and their importance before fusion. First, two-two combinations of modalities are fused at a time and finally, all the modalities are fused to form the trimodal representation feature vector. The experiments are conducted on three standard datasets such as IEMOCAP, CMU-MOSEI, and CMU-MOSI. The proposed model is evaluated using two metrics such as accuracy and F1-Score and the results demonstrate that the proposed model performs better than the standard baselines.
The Computer Journal, 2020
Super-resolution offers a new image with high resolution from the low-resolution (LR) image that ... more Super-resolution offers a new image with high resolution from the low-resolution (LR) image that is highly employed for the numerous remote sensing applications. Most of the existing techniques for formation of the super-resolution image exhibit the loss of quality and deviation from the original multi-spectral LR image. Thus, this paper aims at proposing an efficient super-resolution method using the hybrid model. The hybrid model is developed using the support vector regression model and multi-support vector neural network (MSVNN), and the weights of the MSVNN is tuned optimally using the proposed algorithm. The proposed DolLion algorithm is the integration of the dolphin echolocation algorithm and lion optimization algorithm that exhibits better convergence and offers a global optimal solution. The experimentation is performed using the datasets taken from the multi-spectral scene images. The optimal and effective formation of the super-resolution image using the proposed hybrid ...
International Journal of Engineering and Advanced Technology, 2020
Data visualization is the technique for analyzing the data from the collected dataset. Different ... more Data visualization is the technique for analyzing the data from the collected dataset. Different plots can be drawn for the data visualization. Microscopic images of the liver are being collected as a dataset from the authorized laboratory and the Joint plot, Violin plot and distribution plot are applied on them for the analysis which helps to extract the specific features and for the classification. Joint plot uses the scatter plot and Histogram technique in order to visualize the data. Violin plot technique is used for plotting the numeric data which helps in gray level co-occurrence matrix. Distribution graph is plotted to check the distribution of tones captured in the image so that we can differentiate based on the tones. All three graphs plotted extract the different features which help in efficient analysis.
International Journal of Intelligent Engineering Informatics, 2020
Multimodal affective computing has become a popular research area, due to the availability of a l... more Multimodal affective computing has become a popular research area, due to the availability of a large amount of multimodal content. Feature alignment between the modalities and multimodal fusion are the most important issues in multimodal affective computing. To address these issues, the proposed model extracts the features at word-level and forced alignment is used to understand the time-dependent interaction among the modalities. The contextual information among the words of an utterance and between the nearby utterances is extracted using bidirectional long short term memory (LSTM). Weighted pooling based attention model is used to select the important features within the modalities and importance of each modality. Information from multiple modalities is fused using a cross-modality fusion technique. The performance of the proposed model was tested on two standard datasets such as IEMOCAP and CMU-MOSI. By incorporating the word-level features, feature alignment, and cross-modality fusion, the proposed architecture outperforms the baselines in terms of classification accuracy.
International Journal of Computer Applications, 2019
International Journal of Computer Sciences and Engineering, 2019
International Journal of Fruit Science, 2018
Grading and quality assessment is an important aspect of postharvest management in pomegranate fr... more Grading and quality assessment is an important aspect of postharvest management in pomegranate fruits. In India, the quality assessment is usually performed manually by feeling the fruit in hand. This manual assessment poses a lot of disadvantages such as uncertainty, tediousness, time consumption etc. Moreover there are no well-organized grading systems for testing quality of pomegranates. Aim of the present research work is to eliminate such problems associated with manual quality assessment by incorporating Machine Intelligence and Digital Image Processing techniques. The present work precisely redefines the new quality parameters associated with the existing grading criteria. The research work also proposes a unique Effective Quality Assessment (EQA) algorithm comprising of a holistic approach towards the grading and quality assessment of pomegranate fruits. Results of the research work are found to be 97.83% by using Artificial Neural Networks.
In the fast-paced world of innovation, every breakthrough stands on the shoulders of a collective... more In the fast-paced world of innovation, every breakthrough stands on the shoulders of a collective effort. Patents, the guardians of our ingenious creations, often reflect a synergy of diverse talents and ideas.
But have you ever wondered how many inventors can be credited on a single patent? Is there a limit to this collaborative brilliance?
Discover the answers and gain insights into the world of patents and innovation in my latest article on:
How Many Inventors can be there in a Patent?
Thanks and Regards
Dr Vijay Rajpurohit
www.researchvoyage.com