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With the emergence of deep-learning algorithms, the accuracy of computer-aided supporting systems advanced., However, their adoption in the field of medicine has been limited, partially due to the challenges of generating reliable and timely results. In this research, we focused on classifying four common cutaneous diseases based on dermoscopic images using deep learning algorithms.
The prediction of short term adverse events occurrence in phototherapy treatment is important for the dermatologists who administrate phototherapy to adjust the treatment and standardize the clinical outcomes. Recently, a modeling technique which can detect the potential short term adverse events occurrence in phototherapy treatments is required for clinicians. Based on data mining, this study tends...
Pre-processing steps are critical in automated image analysis systems developed to aid in diagnosis of skin lesion images. The main areas of concern include, but are not limited to, hair on the skin, variations in illumination and skin tone, and alignment of successive skin images. These artifacts can partially or completely obstruct a lesion being analyzed causing errors in classification or diagnosis...
Since the 1990s, fatigue driving has been one of the two main causes of traffic accidents. In order to reduce traffic accidents, many models are applied in the detection of the driver's fatigue. This paper introduces a new model for detecting fatigue driving. This model employs the Hilbert-Huang transforms and the Random Forest Classifier algorithm for the analysis of the three factors, namely, skin...
This paper proposes a face detection algorithm of combining skin color segmentation and AdaBoost algorithm. The algorithm set up the skin Gaussian model in YCbCr color space using skin color clustering characteristics. Then sort out the region of skin color, use AdaBoost algorithm to train a classifier to detect face in the image. Based on our experiments, the proposed method shows good results with...
In practical applications, face detection based on AdaBoost algorithm usually has high false positive rate and missing rate due to the interference of complex background in color images. To address these problems, this paper proposes a face detection method combined skin color segmentation with the AdaBoost algorithm. Firstly, in order to avoid the influence of poor lighting conditions, we use the...
A challenge is indexing the facial beauty by a machine as same evaluated by human beings. A question arises: Can beauty be learnt by machines? Every individual have different concept of facial beauty. Somebody can be attracted by someone but might not be by another person. In recent past, many psychologists, neurologists and other scientists have done tremendous work in this area. This work presents...
The background of the research is to analyze data derived from an elucidation of catfish and carp diseases in Kediri, East Java, Indonesia. The research shows that data about fish's disease history have not been used effectively because it is only be collected. Data about fish's symptom history used by fish trainer only present the number of fish that get disease. Data about fish's history should...
Researchers have developed diverse methods for detecting hand gestures using EMG signal. The signal of EMG sensor can be measured on a human skin surface. There are two approaches to recognizing hand gestures. One approach is to fuse EMG sensor with others sensors. It is possible to extract various motion features. Other approach uses algorithms that improve the recognition accuracy. We survey two...
This paper propose a real-time combined method of Camshift [1] algorithm and Haar-like feature detection [2] for tracking and recognizing hand gesture in images acquired by a possibly moving camera. A Haar-like classifier is used during the initializing of the system to acquire the user's hand color. Camshift algorithm is applied with the acquired color to track the position of the hand, accompanied...
The algorithm is applied to the field of hand gesture recognition by Referencing the Bag of Feature (BoF) algorithm in the field of target recognition and image retrieval. First of all, this paper uses the HSV skin color adaptive method to segment the gesture's information from body and uses SURF algorithm to extract the feature of the image. After feature extraction, it uses BoF algorithm to generate...
Skin color recognition is a useful and popular method in human-computer interaction and also in analyzing the content. In addition, the application programs for recognizing and detecting human body parts, faces, naked people, and retrieving individuals in multimedia databases all make use of skin recognition. Thus, finding a suitable method in order to segment the pixels of an image into different...
Human face detection plays considerably important role in various biometric applications like crowd surveillance, photography, human-computer interaction, tracking, automatic target recognition, artificial intelligence and various security applications. Varying illumination conditions, color variance, brightness, pose variations are major challenging problems for facial detection. Skin color based...
Adaboost is a kind of traversal image searching method, which wastes testing time seriously and should be improved. Skin color detection is used to optimize front-end detection that is relatively stable and has fast speed. In skin color detection, UCS space is used to segment image quickly. Then Adaboost algorithm is used to detect human face based on segmented skin color area. The experiment results...
Skin detection is one of the most important targets of image processing and computer vision. One big concern about skin detection algorithms is their simplicity while keeping a good accuracy in discriminating skin and non-skin pixels. This paper presents a novel and robust skin detector. In this study, statistical information of each pixel and its neighbours were taken into account in order to deal...
Background: A convenient way to analyze quantitatively 11C-PK11195 cerebral PET scans is the simplified reference tissue model (SRTM), which fits Time Activity Curves (TACs) to those of a reference non-pathological region. In this work, we present a fully automatic method which makes use of the expected tracer concentration in 4 predefined tissue classes (gray matter, white matter, blood, high specific...
In order to solve the generalization performance and complex background problems of hand gesture recognition, online dynamic hand recognition with multiple cues is proposed in this paper. The disturbance caused by complex background is reduced by motion detection. As a result of skin color's cluster characteristic, the online skin classifier is constructed by Multi-Gaussian model. The static hand...
A way of combining SVM(Support Vector Machine) with Supervised Subset Density Clustering is proposed in this paper. How to minimize the training set of SVM by means of clustering is researched. Original center positions are of great importance to clustering accuracy. However the traditional clustering center choosing algorithm doesn't work properly when the same kind of samples aren't closely-spaced...
Hand gestures are used widely in communication. An important example is using in the sign languages. Many hand gesture silhouettes are the part of other hand gesture silhouettes. For example, V sign gesture is a part of the high five gesture, because we can create high five gesture silhouettes from the V sign gesture silhouettes by extending the other three fingers. Here we propose the partial contour...
The fatigue level of the driver changes due to many factors such as monotonous job of continuous attentive driving, road traffic, un-healthy road conditions, insufficient sleep, stress level, changing work habits and adverse environmental conditions. This paper provides an alternative approach for design of fatigue classifier for vehicular drivers using Skin Conductance (SC) signal to save the loss...
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