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Over the last two decades, functional Magnetic Resonance Imaging (fMRI) has provided immense data about the dynamics of the brain. Ongoing developments in machine learning suggest improvements in the performance of fMRI data analysis. Clustering is one of the critical techniques in machine learning. Unsupervised clustering techniques are utilized to partition the data objects into different groups...
Extraction of relevant features from high-dimensional multi-way functional MRI (fMRI) data is essential for the classification of a cognitive task. In general, fMRI records a combination of neural activation signals and several other noisy components. Alternatively, fMRI data is represented as a high dimensional array using a number of voxels, time instants, and snapshots. The organisation of fMRI...
Over the past few years, the dimensionality of functional MRI (fMRI) effects the analysis of brain data. In the field of machine learning and statistical analysis, classification of objects plays a significant role. Machine learning classifiers are used to discover the class of new data points from a set of data points. The application of learning techniques on fMRI data alleviates to cognitive state...
Self — organizing natural systems are inspirational to swarm robotics. The applications include social insect systems and social behaviours. The multi — agent tree formation is one of the communication topologies of swarm robotic system. The agents are linked in a tree to communicate with each other through the hierarchy. The focus of this work is to form tree using Transfer Learning (TL) of Reinforcement...
Developing a robust vehicle tracking system is an active area of study in the field of automotive tracking. Such a system is also helpful in providing support to collision avoidance, lane change instructions and merge assistance. Fast Compressive Tracking (FCT) algorithm has recently been proposed for object tracking. FCT has not been explored on vehicle tracking datasets LISA and TME Motorway. In...
Simultaneous Localization and Mapping (SLAM) requires both rotation and scale invariant features. Few algorithms have been developed with rotation and scale invariant features with few limitations. Thus, an algorithm has been proposed to address rotation and scaling invariance. Proposed algorithm Harris-FAST interest point detector is a fusion of Harris and FAST interest point detectors. The detector...
Study and analysis of Hyperspectral data is one of the major research areas in remote sensing technology. Hyperspectral imaging collects information in the form of several hundreds of spectral bands with narrow bandwidths and provides full spectral information regarding the data. Hyperspectral image classification has been a vital topic which is growing rapidly in the field of research. Several applications...
Functional MRI (fMRI) data comprises of a set of trials, each trial is described in terms of a group of 20 to 25 anatomical Region Of Interests (ROI). Each ROI consists of neuroimage sequence information in terms of a set of voxels. Extracting features from ROIs and classifying cognitive states is a challenging task. In this work, average of voxel time horizon for each ROI is considered as an input...
An algorithm is proposed for early detection of Alzheimer's disease and is focused on detecting the condition that would lead to Alzheimer's disease in future. Alzheimer's disease is a prevalent case now and it mostly affects the elderly people. The disease condition makes a person lose his memory and have trouble in doing his day-to-day activities, and progressively the condition leads to death....
Gaze estimation has wide applications in drowsiness detection, security, and biomedical domains. The challenges in estimating the gaze angle include varying light conditions and subtle movements of the gaze. The Convolutional Neural Network (CNN) has recently been suggested as a potential method for gaze estimation. In this present work, we have proposed a gaze estimator combining a neural network...
The complexity of the kidney is that mathematical models of renal function depend on the experimental measurements from in-vivo and in-vitro. Earlier models of the nephron use the simple mathematical model that was unable to clearly capture the pressure-diuresis and pressurenatriuresis functionality. In this paper, a mathematical model of nephron has been developed with isoporous glomerulus model...
A multi-agent flocking control algorithm consisting of leader and agents moving at constant velocity with a method for leader election is proposed in this paper. Due to a faulty leader, connectivity lost between itself and the agents, leading to divergence from trajectory path. Hence, leader election algorithm is developed to replace a faulty leader, thereby regain control of the path of the agents...
An efficient online tracking algorithm to sketch the combined direction and orientation of an object from a video is an arduous task. Existing algorithms updates objects based on the selected features, and hence can't address many of the challenges. Most of the discriminative trackers use a sampling and labelling strategy for the extraction of features, but all those features selected through this...
Classification is a familiar technique used to classify objects. Clustering techniques are employed to segment data into multiple groups. Objects present in clusters exhibit similar characteristics. Machine learning classifiers applied on Functional Magnetic Resonance Imaging (fMRI) data facilitate to classify cognitive states. Clustering methods, such as K-means, Hierarchical, Spectral, and Consensus...
A flocking algorithm using leader-follower strategy is developed, using energy, navigation control and radius of communication. The system consists of multiple agents having varying velocities and second-order dynamics. At any instant the group has one leader. All agents follow this leader, based on the observation of the position and velocity of the leader by a subset of the number of agents. Agents...
One approach, for understanding human brain functioning, is to analyze the changes in the brain while performing cognitive tasks. Towards this, Functional Magnetic Resonance (fMR) images of subjects performing well-defined tasks are widely utilized for task-specific analyses. In this work, we propose a procedure to enable classification between two chosen cognitive tasks, using their respective fMR...
A collision avoidance system is an automobile safety system designed to reduce the severity of an accident. It uses a combination of radar, laser and camera to detect the obstacles and avoid an imminent crash. Being relatively cheap, and capable of giving depth information stereo camera pair alone can be used for obstacle detection. Prime step in obstacle detection by stereo camera system is the generation...
Visual navigation system is widely used in various applications such as traffic surveillance, guidance of autonomous vehicles etc. Object detection is one of the important steps which identifies obstacle and provides information about obstacle's location in the image scenario. Blob detection method has been chosen to detect object and to extract required information about the object. Implementation...
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