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Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Learning robust machine models is still a challenging issue for classifying biomedical data. In order to deal with high dimensionality, low sample size, imbalanced classes, Random Forests (RF) have been widely adopted in this field. RF consists in building a classifier ensemble, with randomization to produce a diverse pool of tree-based classifiers. Since their introduction in 2001 by Leo Breiman,...
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Joint reconstruction and multi-modality/multi-spectral imaging (or joint geophysical inversion) is of growing importance in a wide range of contemporary issues including cost-effective environmental and groundwater investigations, natural hazard monitoring, carbon dioxide sequestration and efficient prediction and extraction of fossil and renewable fuels. It is also emerging rapidly in biomedical...
Hyperspectral imagery, also called imaging spectroscopy, refers to images with a large number (typically a few hundreds) of narrow and contiguous spectral bands, covering a wide range of the electromagnetic spectrum from the visible to the infrared domain. Hyperspectral data is able to provide a very fine description of the chemical components in the sensed materials and ensure their detection, discrimination...
This paper presents a study of speech recognition based on electromyographic biosignals captured from the articulatory muscles in the face using surface electrodes. This paper compares the speech recognition system for spoken English and Malay words by a group of Malay native speakers. Feature extraction was done in both temporal and time-frequency domains. Temporal features used are integrated EMG...
Diabetic macular edema is the leading cause of visual loss for patients with diabetic retinopathy, a complication of diabetes. Early screening and treatment has been shown to prevent blindness in diabetic retinopathy and diabetic macular edema. The Early Treatment Diabetic Retinopathy Study (ETDRS) and the Diabetic Macular Edema Disease Severity Scale are the common screening standards based on the...
The paper presents further research on neural engineering that focuses on the classification of emotional, mental, physical and no stress through the use of Electroencephalography (EEG) signal analysis. Stress is one of the leading causes of several health-related problems and diseases. Therefore, it becomes necessary for people to monitor their stress. The human body acquires and responds to stress...
The most common application for a recognition system of speech signal, finger print, iris, etc. are used for biometrie applications. While other biometric signals like electrocardiogram (ECG) and the Heart Sound (HS) are generally used to identify cluster-related diseases. Nonetheless, performance of a traditional biometric system can be easily compromised as it is prone to spoof attack. This paper...
Fall events are common to elderly people due to their deteriorating muscle structures caused by old age. Their relatively weaker bodies make them prone to accidents such as falls even when performing daily tasks. These fall events may leave physical or psychological consequences among them. Commonly, these events are associated with one or more identifiable risk factors such as weakness, unsteady...
In this paper an efficient approach of fruit maturity classification based on apparent color of the specimen is implemented by the aid of fuzzy inference system (FIS). Heuristically acquired hue and its corresponding saturation and lightness are the attributes of choice, which are utilized to classify the sample into three classes; Raw, Ripe, and Overripe. The membership functions and fuzzy rules...
In general, the three main modules of the color scene classification systems are image decolorization, feature extraction and classification. The work presented in this paper focuses on image decolorization and classification as two stages. The first stage or objective of this paper is to improve the performance of the color scene classification system using deep belief networks (DBN) and support...
Nowadays, QR (quick-response) codes have become part of our daily life. In many applications, QR codes are posted (i.e. pasted or printed) on cylinders. Then, the QR image as captured by a camera would be distorted. In this paper, we try to tackle the decoding of QR codes in such a situation. It is based on perspective projection (PP), which is specified by a camera matrix (cM), with the assistance...
This paper presents a new discriminative learning framework to associate the relationship between the objects and the words in an image and perform template matching scheme for complex association patterns. The problem is first formulated as a bipartite graph matching problem. Thereafter, structural support vector machine (SVM) is employed to obtain the optimal compatibility function to encode the...
Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object. Remote sensing is used in numerous fields, including geography, land surveying and most Earth Science disciplines. In supervised classification, all of the feature extraction methods try to increase the accuracy of classification and simultaneously time of computation. At...
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