In the last years irregular immigration has aroused again due to the fact of war in some regions like middle east and in continents like Africa. Because of that, in this paper we presented a novel solution based in ne...
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ISBN:
(纸本)9783319747187;9783319747170
In the last years irregular immigration has aroused again due to the fact of war in some regions like middle east and in continents like Africa. Because of that, in this paper we presented a novel solution based in new emerging technology to face off the immigration problem focused on the case of sea-type immigration. the presented system is composed by unmanned aerial vehicles (UAV), also known as RPAs or drones, used to fly autonomously over an area in order to detect unallocated potentials immigration boats. the method used is the imageprocessing using combined algorithms and software like OpenCV2 to detect certain patterns in images to determinate whether it is a possible immigration boat or not. Besides, it has been included some prof of concepts to show the effectiveness of the presented system. As main results we was able to determine and detect using aerial pictures if a boat it is a boat with an 82.3% of accuracy (according to the F1 score accuracy test).
In the development of wildlife surveillance system technology, images are important input data that allow real situations in the field to be viewed and analysed. this project proposed a compressed and wireless image t...
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Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agricul...
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ISBN:
(数字)9781510617186
ISBN:
(纸本)9781510617186;9781510617179
Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agriculture. the study aimed to develop a universal method to map total nitrogen content in soil of cultivated land by HSI image at county scale. Several mathematical transformations were used to improve the expression ability of HSI image. the correlations between soil TNC and the reflectivity and its mathematical transformations were analyzed. then the susceptible bands and its transformations were screened to develop the optimizing model of map soil TNC in the Anping County based on the method of multiple linear regression. Results showed that the bands of 14th, 16th, 19th, 37th and 60th with different mathematical transformations were screened as susceptible bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. the determination coefficient of the first order differential of logarithmic transformation was biggest (0.505), while the RMSE was lowest. the study confirmed the first order differential of logarithm transformation as the optimal inversion model for soil TNC, which was used to map soil TNC of cultivated land in the study area.
the main goal of this paper is to present a methodology to design interval observers for discrete-time linear switched systems affected by disturbances and measurement noises which are considered bounded but unknown. ...
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Activated sludge wastewater treatment is a biological wastewater treatment process. Abnormal conditions in the wastewater treatment plant affect the ability of sludge to settle down and reduce the effectiveness of was...
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ISBN:
(数字)9781728150529
ISBN:
(纸本)9781728150536
Activated sludge wastewater treatment is a biological wastewater treatment process. Abnormal conditions in the wastewater treatment plant affect the ability of sludge to settle down and reduce the effectiveness of wastewater treatment. Conventional way of monitoring activated sludge wastewater treatment, through physicochemical measurements, is slow. therefore, image segmentation and analysis provide a faster and cheaper alternative way to monitor the system. In this paper, an imageprocessing algorithm using Gaussian Mixture Modal (GMM) has been proposed to segment microscopic images of wastewater. the segmented images are compared with Otsu thresholding based segmentation and performance is assessed using ground truthimages. Forty bright field microscopic images are used for testing the segmentation accuracy of the proposed algorithm. Out of 40 images, 39 images are successfully segmented. the proposed algorithm achieves an average segmentation accuracy of 99.10%, with 0.0044 false negative rate (FNR) and 0.2209 false positive rate (FPR).
three-dimensional statistical iterative reconstruction (SIR) algorithms have the potential to significantly reduce image artifacts by minimizing a cost function that models the physics and statistics of the data acqui...
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Instagram as an online photo-sharing and social-networking service is becoming more powerful in enabling fashion brands to ramp up their business growth. Nowadays, a single post by a fashion influencer attracts a weal...
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ISBN:
(纸本)9781728111414
Instagram as an online photo-sharing and social-networking service is becoming more powerful in enabling fashion brands to ramp up their business growth. Nowadays, a single post by a fashion influencer attracts a wealth of attention and a magnitude of followers who are curious to know more about the brands and style of each clothing item sitting inside the image. To this end, the development of efficient Deep CNN models that can accurately detect styles and brands have become a research challenge. In addition, current techniques need to cope with inherent fashion-related data issues. Namely, clothing details inside a single image only cover a small proportion of the large and hierarchical space of possible brands and clothing item attributes. In order to cope withthese challenges, one can argue that neural classifiers should become adapted to large-scale and hierarchical fashion datasets. As a remedy, we propose two novel techniques to incorporate the valuable social media textual content to support the visual classification in a dynamic way. the first method is adaptive neural pruning (DynamicPruning) in which the clothing item category detected from posts' text analysis can be used to activate the possible range of connections of clothing attributes' classifier. the second method (DynamicLayers) is a dynamic framework in which multiple-attributes classification layers exist and a suitable attributes' classifier layer is activated dynamically based upon the mined text from the image. Extensive experiments on a dataset gathered from Instagram and a baseline fashion dataset (DeepFashion) have demonstrated that our approaches can improve the accuracy by about 20% when compared to base architectures. It is worth highlighting that with Dynamiclayers we have gained 35% accuracy for the task of multi-class multi-labeled classification compared to the other model.
the proceedings contain 15 papers. the special focus in this conference is on Web and Wireless Geographical Information systems. the topics include: Region-aware route planning;a web interface for exploiting spatio-te...
ISBN:
(纸本)9783319900520
the proceedings contain 15 papers. the special focus in this conference is on Web and Wireless Geographical Information systems. the topics include: Region-aware route planning;a web interface for exploiting spatio-temporal heterogeneous data;increasing maritime situation awareness via trajectory detection, enrichment and recognition of events;from what and when happen, to why happen in air pollution using open big data;A web of data platform for mineral intelligence capacity analysis (MICA);Generation of web-based GIS applications through the reuse of software artefacts;storing and clustering large spatial datasets using big data technologies;An in-depth analysis of CUSUM algorithm for the detection of mean and variability deviation in time series;Application of the KDD process for the visualization of integrated geo-referenced textual data from the pre-processing phase;GeoSPRINGS: Towards a location-aware mobile agent platform;extraction of usage patterns for land-use types by pedestrian trajectory analysis;hierarchical routing techniques in wireless sensor networks;using the internet of things to monitor human and animal uses of industrial linear features.
Power reduction and speedup of computer vision designs remain of high interest as image resolutions continue to increase. Neuromorphic-circuits, emulating the behavior of the nervous system, aspire to achieve this goa...
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ISBN:
(纸本)9781538670996
Power reduction and speedup of computer vision designs remain of high interest as image resolutions continue to increase. Neuromorphic-circuits, emulating the behavior of the nervous system, aspire to achieve this goal. In this paper, we present a pixel-parallel 3D-architecture of a neuromorphic image sensor that uses different sampling frequencies in different regions of an image. We design the model as a bottom-up 3D-architecture composing of several hierarchical computational planes where each plane performs different imageprocessingalgorithms in parallel. the on-chip attention module dynamically detects regions with relevant information and produces a feedback path to sample those regions with a higher clock frequency, whereas regions with low spatial and temporal information receive less attention. the results show that by sampling non-relevant regions with a lower frequency, the sensor can reduce redundancy and enable high-performance computing at low power.
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