Brijesh Verma
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View article: Unified graph-based framework for visual explainability in convolutional neural networks
Unified graph-based framework for visual explainability in convolutional neural networks Open
View article: A Novel Non-iterative Training Method for CNN Classifiers Using Gram–Schmidt Process
A Novel Non-iterative Training Method for CNN Classifiers Using Gram–Schmidt Process Open
Convolutional neural networks have become prominent machine learning models, particularly in the realm of computer vision, due to their ability to predict and extract robust features from raw image data. CNNs, similar to other neural netwo…
View article: Predictive Analytics for Student Success in Higher Education Post-Nep 2020 Implementation Using Data Mining and Machine Learning Techniques
Predictive Analytics for Student Success in Higher Education Post-Nep 2020 Implementation Using Data Mining and Machine Learning Techniques Open
View article: Explainable Image Recognition With Graph-Based Feature Extraction
Explainable Image Recognition With Graph-Based Feature Extraction Open
Deep learning models have proven remarkably adept at extracting salient features from raw data, driving state-of-the-art performance across many domains. However, these models suffer from a lack of interpretability; they function as black …
View article: Parameter Optimisation for Context-Adaptive Deep Layered Network for Semantic Segmentation
Parameter Optimisation for Context-Adaptive Deep Layered Network for Semantic Segmentation Open
Evolutionary optimization methods have been utilized to optimize a wide range of models, including many complex neural network models. Manual parameter selection requires substantial trial and error and specialist domain knowledge of the i…
View article: Context-Adaptive Deep Learning for Efficient Image Parsing in Remote Sensing: An Automated Parameter Selection Approach
Context-Adaptive Deep Learning for Efficient Image Parsing in Remote Sensing: An Automated Parameter Selection Approach Open
Image parsing is among the core tasks in the field of image processing and computer vision having wide-ranging applications in the areas of autonomous driving, image interpretation, medical analysis, and remote sensing. The modern techniqu…
View article: Neural Network Feature Explanation Using Neuron Activation Rate Based Bipartite Graph
Neural Network Feature Explanation Using Neuron Activation Rate Based Bipartite Graph Open
Deep Neural Networks (DNNs) are popular machine learning models that have gained popularity due to its good predictive accuracy and ability to automatically learn features from raw data. Convolutional Neural Networks (CNNs) are one such mo…
View article: A Novel Graph-based Framework for Explainable Image Classification: Features That Matter
A Novel Graph-based Framework for Explainable Image Classification: Features That Matter Open
The efficacy of any machine learning model is largely contingent on the quality of the features used for training. Hence, the extraction of robust and discriminative features from raw data is a critical step. This task, however, presents s…
View article: A Graph-based Context Learning Technique for Image Parsing
A Graph-based Context Learning Technique for Image Parsing Open
The modern deep learning-based architectures have performed well for pixel-wise segmentation tasks. The consideration of context is of vital importance for generation of accurate semantic information. In this research, a deep learning-base…
View article: Novel Automatic Deep Learning Feature Extractor with Target Class Specific Feature Explanations
Novel Automatic Deep Learning Feature Extractor with Target Class Specific Feature Explanations Open
Deep-learning models are popular machine learning models that have gained their popularity in various fields of computer vision, natural language processing etc, due to their excellent predictive accuracy and ability to automatically extra…
View article: A Novel Explainable Deep Learning Model with Class Specific Features
A Novel Explainable Deep Learning Model with Class Specific Features Open
View article: A Novel Optimized Context-Based Deep Architecture for Scene Parsing
A Novel Optimized Context-Based Deep Architecture for Scene Parsing Open
View article: Genetic Algorithms for Optimising Context-based Neural Networks for Image Segmentation
Genetic Algorithms for Optimising Context-based Neural Networks for Image Segmentation Open
Image segmentation is one of the major challenges in real-world computer vision applications. Context-embedded network models proposed for image segmentation have outperformed context-free models. However, optimized values of many paramete…
View article: Relationship aware context adaptive deep learning for image parsing
Relationship aware context adaptive deep learning for image parsing Open
View article: Context-based Deep Learning Architecture with Optimal Integration Layer for Image Parsing
Context-based Deep Learning Architecture with Optimal Integration Layer for Image Parsing Open
Deep learning models have been efficient lately on image parsing tasks. However, deep learning models are not fully capable of exploiting visual and contextual information simultaneously. The proposed three-layer context-based deep archite…
View article: Deep Learning Model with GA based Feature Selection and Context Integration
Deep Learning Model with GA based Feature Selection and Context Integration Open
Deep learning models have been very successful in computer vision and image processing applications. Since its inception, Many top-performing methods for image segmentation are based on deep CNN models. However, deep CNN models fail to int…
View article: Road Severity Distance Calculation Technique Using Deep Learning Predictions in 3-D Space
Road Severity Distance Calculation Technique Using Deep Learning Predictions in 3-D Space Open
Some roadside objects pose a significant danger to pedestrians and vehicles when they are too close to the road. A few examples are trees, poles and fences. Their proximity to the road can change over time due to natural conditions or huma…
View article: Fully Convolutional Neural Network with Relation Aware Context Information for Image Parsing
Fully Convolutional Neural Network with Relation Aware Context Information for Image Parsing Open
Image parsing is among the core tasks in the field of computer vision. The automatic pixel-wise segmentation offers great potential in terms of application adaptability. Traditional convolutional networks have produced better segmentation …
View article: Prediction of Students’ Performance in e-Learning Environment using Data Mining/ Machine Learning Techniques
Prediction of Students’ Performance in e-Learning Environment using Data Mining/ Machine Learning Techniques Open
The COVID-19 pandemic has drastically changed the way od of learning. During this pandemic the learning has shifted from offline to online. student’s performance prediction based on their relevant information has emerged new area for educa…
View article: Optimization of Fully Convolutional Network for Road Safety Attribute Detection
Optimization of Fully Convolutional Network for Road Safety Attribute Detection Open
Even though, deep learning techniques demonstrate an outstanding performance in various applications, success of deep learning techniques depends upon appropriately setting their parameters in achieving most accurate results. Therefore, in…
View article: Multicluster Class-Balanced Ensemble
Multicluster Class-Balanced Ensemble Open
Ensemble classifiers using clustering have significantly improved classification and prediction accuracies of many systems. These types of ensemble approaches create multiple clusters to train the base classifiers. However, the problem wit…
View article: A Novel Diversity Measure and Classifier Selection Approach for Generating Ensemble Classifiers
A Novel Diversity Measure and Classifier Selection Approach for Generating Ensemble Classifiers Open
Accuracy and diversity are considered to be the two deriving factors when it comes to generating an ensemble classifier. Focusing only on accuracy causes the ensemble classifier to suffer from diminishing returns and the ensemble accuracy …
View article: In Field Fruit Sizing Using A Smart Phone Application
In Field Fruit Sizing Using A Smart Phone Application Open
In field (on tree) fruit sizing has value in assessing crop health and for yield estimation. As the mobile phone is a sensor and communication rich device carried by almost all farm staff, an Android application (“FruitSize”) was developed…
View article: Density Weighted Connectivity of Grass Pixels in image frames for biomass estimation
Density Weighted Connectivity of Grass Pixels in image frames for biomass estimation Open
View article: Monthly Rainfall Forecasting Using One-Dimensional Deep Convolutional Neural Network
Monthly Rainfall Forecasting Using One-Dimensional Deep Convolutional Neural Network Open
Rainfall prediction targets the determination of rainfall conditions over a specific location. It is considered vital for the agricultural industry and other industries. In this paper, we propose a new forecasting method that uses a deep c…
View article: On-Tree Mango Fruit Size Estimation Using RGB-D Images
On-Tree Mango Fruit Size Estimation Using RGB-D Images Open
In-field mango fruit sizing is useful for estimation of fruit maturation and size distribution, informing the decision to harvest, harvest resourcing (e.g., tray insert sizes), and marketing. In-field machine vision imaging has been used f…
View article: Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond
Editorial IEEE Transactions on Neural Networks and Learning Systems 2016 and Beyond Open
“Happy New Year!” At the beginning of 2016, I would like to take this opportunity to wish everyone a very happy, healthy, and prosperous new year! It is my great honor and privilege to serve as the Editor-in-Chief (EiC) of the IEEE TRANSAC…
View article: Segmentation of Geophysical Data: A Big Data Friendly Approach
Segmentation of Geophysical Data: A Big Data Friendly Approach Open
A new scalable segmentation algorithm is proposed in this paper for the forensic determination of level shifts in geophysical time series. While a number of segmentation algorithms exist, they are generally not ‘big data friendly’ due eith…