In this work, we propose an automated system for the personalization of retina laser treatment in diabetic retinopathy. The system comprises fundus images processing methods, algorithms for photocoagulation pattern ma...
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Detecting objects in space that are potentially hazardous to satellites or our population is an important problem that is growing every year as more objects are launched and collisions between objects introduce more d...
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ISBN:
(纸本)9781628410228
Detecting objects in space that are potentially hazardous to satellites or our population is an important problem that is growing every year as more objects are launched and collisions between objects introduce more debris. The problem of detecting these objects using Earth-based optical telescopes is challenging, but is generally dictated by available light and atmospheric seeing conditions. In this paper a related problem is described and demonstrated involving the detection of objects that are near brighter objects like stars. Starlight creates the expected problem of increasing the amount of noise and extra light in the region around it, but in this paper the effect of spatial operations carried out by traditional space object detection algorithms is factored in. These spatial processing effects magnify the contribution of stray starlight and cause large zones around stars to form that make detection of any space debris within them very difficult. This paper documents a new algorithm that can mitigate this effect and facilitate the detection of objects near stars.
This research study analyzes the multidimensional landscape of steganography, examining its historical roots, theoretical background, contemporary approaches, and various applications. Beginning with a historical over...
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ISBN:
(纸本)9798350391558;9798350379990
This research study analyzes the multidimensional landscape of steganography, examining its historical roots, theoretical background, contemporary approaches, and various applications. Beginning with a historical overview, this study investigates the evolution of steganography from its ancient roots to its present iterations in the digital world. Next, the study progresses towards analyzing the fundamental principles and theoretical frameworks that underpin steganographic systems, such as cryptography and digital signal processing. Finally, this study presents a thorough evaluation of contemporary steganographic technologies, which range from simple LSB (Least Significant Bit) substitution techniques to advanced adaptive algorithms and machine learning methods by including deep-learning based steganography and coverless steganography. Notably, this study identifies key challenges, including detection resistance, payload capacity, and robustness against attacks. Overall, this study presents a thorough understanding of steganography, emphasizing its significance as a versatile tool for communication in the digital era, while also highlighting the challenges that pave way for future innovations.
The proceedings contain 50 papers. The topics discussed include: a rational multiparty information exchange model using extensive games;RSS-based secret key generation for indoor and outdoor WBANs using on-body sensor...
ISBN:
(纸本)9781509017775
The proceedings contain 50 papers. The topics discussed include: a rational multiparty information exchange model using extensive games;RSS-based secret key generation for indoor and outdoor WBANs using on-body sensor nodes;robust spectrum sensing algorithms under noise uncertainty;multicarrier modulation for HFe MANET in the Presence of communications;joint protection of a military formation using heterogeneous sensors in a mobile ad hoc network: concept and field tests;learning multi-channel power allocation against smart jammer in cognitive radio networks;and complex event processing for content-based text, image, and video retrieval.
A new algorithm for watermarking sequence generation is proposed, allowing collision-free robust watermarking using correlation-based watermark detector with known detection threshold. The proposed algorithm provides ...
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Traditional motion capture systems are prone to environmental interference, resulting in noise and errors in the captured data. This article proposes an artificial intelligence oriented intelligent processing algorith...
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The conference materials contain 213 papers. The following topics are dealt with: vision and imageprocessing;neural network algorithms;enterprise modeling and simulation;knowledge-based systems;telerobotics;decision-...
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ISBN:
(纸本)0879425970
The conference materials contain 213 papers. The following topics are dealt with: vision and imageprocessing;neural network algorithms;enterprise modeling and simulation;knowledge-based systems;telerobotics;decision-support systems;adaptive and learning systems;knowledge engineering frameworks;autonomous systems;telecommunications;cognitive modeling and learning systems;team coordination and decision making;fuzzy logic theory and applications;automation in manned systems;software internationalization;human-computer cooperation;manual control;neural network vision;concurrent engineering and manufacturing systems;robotic systems;visual programming and advanced user interfaces;neural network hardware;computer-aided systems engineering;AI for space applications;adaptation;cognitive modeling and human-computer integration;enterprise modeling and simulation;expert decision systems;team performance and distributed problem solving;biological cybernetics.
Extraction of blood vessels from retinal fundus images is a primary phase in the diagnosis of several eye disorders including diabetic retinopathy, a leading cause of vision impairment among working-age adults globall...
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ISBN:
(纸本)9789811078712;9789811078705
Extraction of blood vessels from retinal fundus images is a primary phase in the diagnosis of several eye disorders including diabetic retinopathy, a leading cause of vision impairment among working-age adults globally. Since manual detection of blood vessels by ophthalmologists gets progressively difficult with increasing scale, automated vessel detection algorithms provide an efficient and cost-effective alternative to manual methods. This paper aims to provide an efficient and highly accurate algorithm for the extraction of retinal blood vessels. The proposed algorithm uses morphological processing, background elimination, neighborhood comparison for preliminary detection of the vessels. Detection and removal of fovea, and bottom-hat filtering are performed subsequently to improve the accuracy, which is then calculated as a percentage with respect to ground truth images.
Digital breast tomosynthesis (DBT) has superior detection performance than mammography (DM) for population-based breast cancer screening, but the higher number of images that must be reviewed poses a challenge for its...
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ISBN:
(数字)9781510616400
ISBN:
(纸本)9781510616400
Digital breast tomosynthesis (DBT) has superior detection performance than mammography (DM) for population-based breast cancer screening, but the higher number of images that must be reviewed poses a challenge for its implementation. This may be ameliorated by creating a two-dimensional synthetic mammographic image (SM) from the DBT volume, containing the most relevant information. When creating a SM, it is of utmost importance to have an accurate lesion localization detection algorithm, while segmenting fibroglandular tissue could also be beneficial. These tasks encounter an extra challenge when working with images in the medio-lateral oblique view, due to the presence of the pectoral muscle, which has similar radiographic density. In this work, we present an automatic pectoral muscle segmentation model based on a u-net deep learning architecture, trained with 136 DBT images acquired with a single system (different BIRADS densities and pathological findings). The model was tested on 36 DBT images from that same system resulting in a dice similarity coefficient (DSC) of 0.977 (0.967-0.984). In addition, the model was tested on 125 images from two different systems and three different modalities (DBT, SM, DM), obtaining DSCs between 0.947 and 0.970, a range determined visually to provide adequate segmentations. For reference, a resident radiologist independently annotated a mix of 25 cases obtaining a DSC of 0.971. The results suggest the possibility of using this model for inter-manufacturer DBT, DM and SM tasks that benefit from the segmentation of the pectoral muscle, such as SM generation, computer aided detection systems, or patient dosimetry algorithms.
Operational requirements for naval applications have shifted towards the fast, reliable detection and avoidance or elimination of underwater threats (e.g. mines, IEDs (improvised explosive devices), ...) over the last...
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ISBN:
(纸本)9781424425228
Operational requirements for naval applications have shifted towards the fast, reliable detection and avoidance or elimination of underwater threats (e.g. mines, IEDs (improvised explosive devices), ...) over the last decade. For these purposes the ability to reliable separate mines or IEDs from rocks or bottom features is essential. This separation can be much more difficult for IEDs compared to traditional cylindrical or spherical mines. Furthermore, automatic target recognition (ATR) approaches are gaining more and more importance for autonomous UUVs. Since no operator is in the loop, these systems are harmed by a limited number of missed detections or a significant number of false targets. In this context the ability to automatically detect and classify objects depends directly on the true resolution of the acoustic imaging system. All this points towards the need for a high resolution sensor for reliable object detection, classification and identification. Starting with some examples, this paper presents theoretical considerations about the required resolution for the detection, classification and identification process of objects in side scan sonar images. Clues for the required resolution can be directly derived from the Johnson-Criterion for electro-optics systems [1]. Secondly, an imageprocessing software for automatic object detection and classification currently under development at FWG with the assistance of FU-Berlin and FGAN-FOM is presented. This part focuses on an overview of the system and recently developed and tested algorithms. Before applying different detection algorithms, the side scan sonar images are preprocessed including normalization, height estimation plus slant range correction and geo-referencing. Different normalization algorithms can be used. Currently six different screening algorithms for detecting regions of interests (ROIs) with objects of interest are implemented. These screening algorithms base on statistical features within a
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