Search Results for author:
Found 36 papers, 1 papers with code
OrthoSeisnet: Seismic Inversion through Orthogonal Multi-scale Frequency Domain U-Net for Geophysical Exploration
However, the detection of sparse thin layers within seismic datasets presents a significant challenge due to the ill-posed nature and poor non-linearity of the problem.
LATIS: Lambda Abstraction-based Thermal Image Super-resolution
Single image super-resolution (SISR) is an effective technique to improve the quality of low-resolution thermal images.
Sparse algorithms for EEG source localization
In this article, a comprehensive review of the state of the art sparse source localization methods in this field is presented.
Illumination-invariant Face recognition by fusing thermal and visual images via gradient transfer
An algorithm is proposed to implement fusion of thermal and visual images.
A Semi-supervised Spatial Spectral Regularized Manifold Local Scaling Cut With HGF for Dimensionality Reduction of Hyperspectral Images
The underlying idea of the proposed method is to exploit the limited labeled information from both the spectral and spatial domains along with the abundant unlabeled samples to facilitate the classification task by retaining the original distribution of the data.
ESCaF: Pupil Centre Localization Algorithm with Candidate Filtering
A simple tracking scheme has also been added which improves the processing speed.
A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image
The underlying idea of this method is to generate the optimal projection matrix by considering both the sparsity as well as the correlation of the data samples.
A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images
The underlying idea of this method is to obtain a linear projection matrix by solving a nonlinear objective function based on the intrinsic geometrical structure of the data.
Recognition of Activities from Eye Gaze and Egocentric Video
This paper presents a framework for recognition of human activity from egocentric video and eye tracking data obtained from a head-mounted eye tracker.
Graph Scaling Cut with L1-Norm for Classification of Hyperspectral Images
The underlying idea of this method is to generate the optimal projection matrix by retaining the original distribution of the data.
Classification Of Hyperspectral Images
Dimensionality Reduction
+1
An Effective Feature Selection Method Based on Pair-Wise Feature Proximity for High Dimensional Low Sample Size Data
However, the efficacy of the selection criteria for low sample size applications is neglected in most cases.
An Unsupervised Approach for Overlapping Cervical Cell Cytoplasm Segmentation
The poor contrast and the overlapping of cervical cell cytoplasm are the major issues in the accurate segmentation of cervical cell cytoplasm.
A Novel Framework based on SVDD to Classify Water Saturation from Seismic Attributes
Thus, satisfactory classification of water saturation from seismic attributes is beneficial for reservoir characterization.
A novel multiclassSVM based framework to classify lithology from well logs: a real-world application
Therefore, in case of a multiclass problem, the problem is divided into a series of binary problems which are solved by binary classifiers, and finally the classification results are combined following either the one-against-one or one-against-all strategies.
Development of a hybrid learning system based on SVM, ANFIS and domain knowledge: DKFIS
The classification results have been further fine-tuned applying expert knowledge based on the relationship among predictor variables i. e. well logs and target variable - oil saturation.
A One class Classifier based Framework using SVDD : Application to an Imbalanced Geological Dataset
Evaluation of hydrocarbon reservoir requires classification of petrophysical properties from available dataset.
Real-time Eye Gaze Direction Classification Using Convolutional Neural Network
We propose a real-time framework for the classification of eye gaze direction and estimation of eye accessing cues.
Fast and Accurate Algorithm for Eye Localization for Gaze Tracking in Low Resolution Images
A two-stage algorithm is proposed for iris centre localization.
A Score-level Fusion Method for Eye Movement Biometrics
Features extracted from fixations and saccades are used by a Gaussian Radial Basis Function Network (GRBFN) based method for biometric authentication.
Ranked #1 on
Person Identification
on BioEye
The Indian Spontaneous Expression Database for Emotion Recognition
However, currently there is a huge demand for spontaneous expression databases for the pragmatic implementation of the facial expression recognition algorithms.
A Novel Pre-processing Scheme to Improve the Prediction of Sand Fraction from Seismic Attributes using Neural Networks
The network yielding satisfactory performance in the validation stage is used to predict lithological properties from seismic attributes throughout a given volume.
Quantification of sand fraction from seismic attributes using Neuro-Fuzzy approach
Though seismic data is helpful in extrapolation of reservoir properties away from boreholes; yet, it could be challenging to delineate thin sand and shale reservoirs using seismic data due to its limited resolvability.
Well Tops Guided Prediction of Reservoir Properties using Modular Neural Network Concept A Case Study from Western Onshore, India
The data set used in this study comprising three seismic attributes and well log data from eight wells, is acquired from a western onshore hydrocarbon field of India.
SPECFACE - A Dataset of Human Faces Wearing Spectacles
This paper presents a database of human faces for persons wearing spectacles.
An Improved Algorithm for Eye Corner Detection
In this paper, a modified algorithm for the detection of nasal and temporal eye corners is presented.
Evaluation of Denoising Techniques for EOG signals based on SNR Estimation
This paper evaluates four algorithms for denoising raw Electrooculography (EOG) data based on the Signal to Noise Ratio (SNR).
Fast Computation of PERCLOS and Saccadic Ratio
This thesis describes the development of fast algorithms for the computation of PERcentage CLOSure of eyes (PERCLOS) and Saccadic Ratio (SR).
Design and Implementation of Real-time Algorithms for Eye Tracking and PERCLOS Measurement for on board Estimation of Alertness of Drivers
Local Binary Pattern (LBP) histogram based method is used for the detection of eyes at night time.
Comparative Evaluation of Symmetric SVD Algorithms for Real-time Face and Eye Tracking
Therefore, fast SVD of image covariance matrix at various levels of resolution needs to be carried out to generate the eigen database.
Numerical Analysis Numerical Analysis
A Real Time Facial Expression Classification System Using Local Binary Patterns
A customizable approach is proposed for facial expression analysis, since the various expressions and intensity of expressions vary from person to person.
Automatic Facial Expression Recognition Using Features of Salient Facial Patches
These active patches are further processed to obtain the salient patches which contain discriminative features for classification of each pair of expressions, thereby selecting different facial patches as salient for different pair of expression classes.
Facial Expression Recognition
Facial Expression Recognition (FER)
+2
Robust Facial Expression Classification Using Shape and Appearance Features
Feature extraction is one important step in expression analysis which contributes toward fast and accurate expression recognition.
A Vision Based System for Monitoring the Loss of Attention in Automotive Drivers
In this paper, we propose a robust real time embedded platform to monitor the loss of attention of the driver during day as well as night driving conditions.
A Framework for Fast Face and Eye Detection
Face detection is an essential step in many computer vision applications like surveillance, tracking, medical analysis, facial expression analysis etc.
Dynamic Model of Facial Expression Recognition based on Eigen-face Approach
In this paper, a holistic approach for facial expression recognition is proposed which captures the variation in facial features in temporal domain and classifies the sequence of images in different emotions.
