AUTOMATED DIAGNOSIS OF GLAUCOMA USING EMPIRICAL WAVELET TRANSFORM AND CORRENTROPY FEATURES EXTRACTED FROM FUNDUS IMAGES

AUTOMATED DIAGNOSIS OF GLAUCOMA USING EMPIRICAL WAVELET TRANSFORM AND CORRENTROPY FEATURES EXTRACTED FROM FUNDUS IMAGES AUTOMATED DIAGNOSIS OF GLAUCOMA USING EMPIRICAL WAVELET TRANSFORM AND CORRENTROPY FEATURES EXTRACTED FROM FUNDUS IMAGES. Glaucoma is the second leading cause of blindness worldwide. The available scanning methods are Heidelberg Retinal Tomography (HRT), Scanning Laser Polarimetry … Continue Reading →

Orthogonal frequency division multiplexing (OFDM)

Orthogonal frequency division multiplexing (OFDM) Orthogonal frequency division multiplexing (OFDM) is one of the multi-carrier modulation (MCM) techniques that transmit signals through multiple carriers. These carriers (subcarriers) have different frequencies and they are orthogonal to each other. Orthogonal frequency division multiplexing techniques have been applied in both wired and wireless … Continue Reading →

Combination Strategies in abdominal Multi-Atlas Image Segmentation

Combination Strategies in abdominal Multi-Atlas Image Segmentation Combination Strategies in abdominal Multi-Atlas Image Segmentation. The segmentation of organs like the liver, pancreas, and kidneys on abdominal computed tomography (CT) scans can form an input to computer aided diagnosis (CAD) systems and laparoscopic surgery assistance. We display a common, fully automated technique … Continue Reading →

Backward registration based objective quality assessment for image re targeting

Backward registration based objective quality assessment for image re targeting Backward registration based objective quality assessment for image re targeting. This paper show the result of a recent large-scale subjective study of image retargeting quality on a collection of images produced by several representative image retargeting techniques. In this paper, … Continue Reading →

Deep Neural Networks (DNNs)

Deep Neural Networks (DNNs) Deep Neural Networks (DNNs) are extremely powerful in performing machine learning tasks including image classification, speech recognition, and speech coding . However, training DNNs is computationally difficult. In particular, fine tuning DNNs requires stochastic gradient descent, which is unusually difficult to parallelize across machines. This lack … Continue Reading →

Automatic screening and classification of diabetic retinopathy using filter banks.

Automatic screening and classification of diabetic retinopathy using filter banks. Automatic screening and classification of diabetic retinopathy using filter banks.The effects of the eye abnormalities are mostly gradual in nature which shows the necessity for an accurate abnormality identification system. Abnormality in retina is one among them. Most of the … Continue Reading →

ECG ANALYSIS AND CLASSIFICATION OF ARRHYTHMIA

ECG ANALYSIS AND CLASSIFICATION OF ARRHYTHMIA ECG ANALYSIS AND CLASSIFICATION OF ARRHYTHMIA . Automatic recognition of cardiac arrhythmia is important for diagnosis of cardiac anomalies. Therefore, in this study, an expert system for Electrocardiogram (ECG) arrhythmia classification is proposed. The electrocardiogram (ECG) is a graphical recording of the electrical signals … Continue Reading →

Optimal Pricing and Load Sharing for Energy Saving With Cooperative Communications

Optimal Pricing and Load Sharing for Energy Saving With Cooperative Communications Optimal Pricing and Load Sharing for Energy Saving With Cooperative Communications. Cooperative communications has long been proposed as an effective method for reducing the energy consumption of the mobile terminals (MTs) in wireless cellular networks. However, it is hard … Continue Reading →