In the past three years, deep convolutional neural networks (DCNNs) have achieved promising results in detecting skin cancer. However, improving the accuracy and efficiency of the automatic detection of melanoma is st...
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ISBN:
(纸本)9781728126036
In the past three years, deep convolutional neural networks (DCNNs) have achieved promising results in detecting skin cancer. However, improving the accuracy and efficiency of the automatic detection of melanoma is still urgent due to the visual similarity of benign and malignant dermoscopic images. There is also a need for fast and computationally effective systems for mobile applications targeting caregivers and homes. This paper presents the You Only Look Once (Yolo) algorithms, which are based on DCNNs applied to the detection of melanoma. The Yolo algorithms comprise YoloV1, YoloV2, and YoloV3, whose methodology first resets the input image size and then divides the image into several cells. According to the position of the detected object in the cell, the network will try to predict the bounding box of the object and the class confidence score. Our test results indicate that the mean average precision (mAP) of Yolo can exceed 0.82 with a training set of only 200 images, proving that this method has great advantages for detecting melanoma in lightweight system applications.
Optical remote sensing images contain cloud pixels, which need to be detected and masked for different earth observation studies and applications. In literature, various algorithms are reported which can detect cloud ...
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ISBN:
(数字)9781728185248
ISBN:
(纸本)9781728185255
Optical remote sensing images contain cloud pixels, which need to be detected and masked for different earth observation studies and applications. In literature, various algorithms are reported which can detect cloud in multi-spectral remote sensing images. In this paper, we have developed an approach based on spectral angle computation that measures the radiometric gap between a reference pixel and input image pixels. Reference spectra is determined using mode seeking technique by taking multiple cloud pixels from multi-temporal images covering different land terrain. The processing chain is developed and tested in Resourcesat LISS-3 surface reflectance data. Result section shows that technique developed can determine thick cloud pixels with high confidence interval and compared with other novel cloud detection methods.
A signature is a legal representation of a person. Forgers take advantage of this fact as they copy and imitate signatures for their own benefit. People could lose money or properties with their forged signatures used...
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ISBN:
(纸本)9781450361033
A signature is a legal representation of a person. Forgers take advantage of this fact as they copy and imitate signatures for their own benefit. People could lose money or properties with their forged signatures used to close a contract, or to withdraw from banks. With this in mind, the researchers developed inSignia, a mobile application that could help possible victims of forgery. InSignia verifies signatures for authenticity and forgery using smartphone cameras and images. The study uses BRISK, or Binary Robust Invariant Scale Keypoints, a feature detector algorithm in comparing images. The mobile application allows image storage through a profile list, collecting, and saving significant signature images that can be compared to another signature image for authenticity. The study used Mobile Software Development Model (MDSM) as the project development methodology, which tolerated simultaneous testing and development of the application, as well as concept changes. The mobile application was subjected to stress and field testings. With the use of ISO/IEC 2011 25010: systems and software engineering - systems and software Quality Requirements and Evaluation (SQuaRE), the application was evaluated in terms of its functionality, usability, reliability, and efficiency. Based on the evaluation results, the application satisfied the respondents and possible users, with an overall mean rating 4.16 or 'Very Acceptable'.
Co-registrating is a common pre-processing step for existing change detection algorithms, but registering bi-temporal images is nontrivial. The use of image patch as input for deep learning techniques provides a natur...
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ISBN:
(纸本)9781450369091
Co-registrating is a common pre-processing step for existing change detection algorithms, but registering bi-temporal images is nontrivial. The use of image patch as input for deep learning techniques provides a natural avenue to apply them in the OBIA framework, and have shown successful performance in the object-based land cover mapping and change detection applications. Even though attempts of applying deep learning techniques for change detection applications have been made with varying success, its application under OBIA framework for change detection have not been conducted and its tolerance for misregistration among temporal images are neither known. This study performed change detection under OBIA framework using deep learning techniques for the first time, and evaluated its performance regarding their tolerance of image misregistration on training and testing dataset. Our results demonstrate the proposed change detection scheme is surprisingly robust to image misregistration on the testing dataset, while classifiers trained with the training dataset containing image misregistration errors suffer from slight decrease of overall accuracy.
Hand gestures offer humans a natural way to interact with computers for a variety of applications. However, factors such as the complexity of hand gesture patterns, size differences, hand posture, and environmental li...
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The improvement of digital imageprocessing technology is increasingly rapid. imageprocessing has been widely used to maximize the usefulness of the webcam interface or CCTV, which can be used to monitor traffic flow...
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Multi-aperture imaging systems are one of the modern trends for imaging devices. The paper presents the results of developing a multi-aperture imaging system based on single diffractive lenses and postprocessing pipel...
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Wine label information was found to have a positive effect on consumer choice. However, it is not easy for consumers to read the information on wine labels since these texts are usually not print in English. Wine labe...
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The security of information is required by internet technologies and its application during transmission over the nonsecured communication channel. Steganography means is to hide secret data into another media file. I...
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Advertisement is an integral part of the daily life in modern society. Nevertheless, the advertising industry often ignores the fact that people might understand ads differently and behave accordingly. Eye movements, ...
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ISBN:
(纸本)9783319911892
Advertisement is an integral part of the daily life in modern society. Nevertheless, the advertising industry often ignores the fact that people might understand ads differently and behave accordingly. Eye movements, fixation times, gaze landing sites and areas of interest in visual images are known as good predictors of customer behavior. Here we perform eye tracking of several versions (neutral, positively and negatively valence) of popular ads and analyze the dependency of eye fixation times on affective and gender factors. The results show that there are statistically significant differences on how affectively charged images are perceived, but no statistically significant differences between genders have been found when shorter fixations representing unconscious processing of visual information are analyzed.
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