His primary areas of study are Artificial intelligence, Mathematical optimization, Thresholding, Segmentation and Pattern recognition. Suresh Chandra Satapathy regularly ties together related areas like Machine learning in his Artificial intelligence studies. His Mathematical optimization research focuses on subjects like Benchmark, which are linked to Evolutionary computation, Function optimization problems and Global optimization problem.
His Segmentation research includes elements of Tsallis entropy and Entropy. In general Pattern recognition, his work in Principal component analysis, Softmax function, Feature vector and Support vector machine is often linked to Pneumonia linking many areas of study. Suresh Chandra Satapathy has researched Image processing in several fields, including Otsu's method, Image segmentation, Firefly algorithm and Bat algorithm.
His primary areas of study are Artificial intelligence, Pattern recognition, Machine learning, Cluster analysis and Mathematical optimization. His study looks at the intersection of Artificial intelligence and topics like Particle swarm optimization with Differential evolution. His Pattern recognition study combines topics from a wide range of disciplines, such as Entropy and Preprocessor.
Many of his studies involve connections with topics such as Software and Machine learning. His research on Cluster analysis frequently links to adjacent areas such as Data mining. His work on Optimization problem and Evolutionary algorithm as part of his general Mathematical optimization study is frequently connected to Teaching learning, thereby bridging the divide between different branches of science.
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Convolutional neural network, Machine learning and Deep learning. His Artificial intelligence study focuses mostly on Support vector machine, Pooling, Feature extraction, Segmentation and Thresholding. The concepts of his Thresholding study are interwoven with issues in Ground truth, Active contour model and Magnetic resonance imaging.
Suresh Chandra Satapathy interconnects Entropy, Local binary patterns and Noise reduction in the investigation of issues within Pattern recognition. He has included themes like Classifier and Class in his Machine learning study. His study in Deep learning is interdisciplinary in nature, drawing from both Computer security and Cryptocurrency.
Suresh Chandra Satapathy focuses on Artificial intelligence, Pattern recognition, Convolutional neural network, Deep learning and Machine learning. The study of Artificial intelligence is intertwined with the study of Genetic algorithm in a number of ways. His work in the fields of Segmentation overlaps with other areas such as Lung cancer.
His Convolutional neural network study combines topics in areas such as Feature extraction and Cohen's kappa. In his work, Random forest, Transfer of learning, Nevi and melanomas and Residual neural network is strongly intertwined with Support vector machine, which is a subfield of Deep learning. His studies deal with areas such as Atypical nevus, Nevus, Medical diagnosis and Hidden Markov model as well as Machine learning.
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Cloud Computing: Security Issues and Research Challenges
Rabi Prasad Padhy;Manas Ranjan Patra;Suresh Chandra Satapathy;Oracle India Pvt.
Entropy based segmentation of tumor from brain MR images a study with teaching learning based optimization
V. Rajinikanth;Suresh Chandra Satapathy;Steven Lawrence Fernandes;S. Nachiappan.
Pattern Recognition Letters (2017)
Multi-level image thresholding using Otsu and chaotic bat algorithm
Suresh Chandra Satapathy;N. Sri Madhava Raja;V. Rajinikanth;Amira S. Ashour.
Neural Computing and Applications (2018)
Internet of Things and Big Data Analytics Toward Next-Generation Intelligence
Nilanjan Dey;Aboul Ella Hassanien;Chintan Bhatt;Amira S. Ashour.
Social group optimization (SGO): a new population evolutionary optimization technique
Suresh Satapathy;Anima Naik.
Complex & Intelligent Systems (2016)
Data clustering based on teaching-learning-based optimization
Suresh Chandra Satapathy;Anima Naik.
swarm evolutionary and memetic computing (2011)
A teaching learning based optimization based on orthogonal design for solving global optimization problems.
Suresh Chandra Satapathy;Anima Naik;K Parvathi.
Modified Teaching–Learning-Based Optimization algorithm for global numerical optimization—A comparative study
Suresh Chandra Satapathy;Anima Naik.
Swarm and evolutionary computation (2014)
Segmentation of Ischemic Stroke Lesion in Brain MRI Based on Social Group Optimization and Fuzzy-Tsallis Entropy
V. Rajinikanth;Suresh Chandra Satapathy.
Arabian Journal for Science and Engineering (2018)
Design and Implementation of a Cloud based Rural Healthcare Information System Model
Rabi Prasad Padhy;Manas Ranjan Patra;Suresh Chandra Satapathy.
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