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ردیف | عنوان | نوع |
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51 |
Assessing surface drainage conditions at the street and neighborhood scale: A computer vision and flow direction method applied to lidar data
ارزیابی شرایط زهکشی سطحی در مقیاس خیابان و محله: یک روش دید کامپیوتری و جهت جریان اعمال شده به داده های لیدار-2022 Surface drainage at the neighborhood and street scales plays an important role in conveying stormwater and
mitigating urban flooding. Surface drainage at the local scale is often ignored due to the lack of up-to-date fine-
scale topographical information. This paper addresses this issue by providing a novel method for evaluating
surface drainage at the neighborhood and street scales based on mobile lidar (light detection and ranging)
measurements. The developed method derives topographical properties and runoff accumulation by applying a
semantic segmentation (SS) model (a computer vision technique) and a flow direction model (a hydrology
technique) to lidar data. Fifty lidar images representing 50 street blocks were used to train, validate, and test the
SS model. Based on the test dataset, the SS model has 80.3% IoU and 88.5% accuracy. The results suggest that the
proposed method can effectively evaluate surface drainage conditions at both the neighborhood and street scales
and identify problematic low points that could be susceptible to water ponding. Municipalities and property
owners can use this information to take targeted corrective maintenance actions. keywords: تقسیم بندی معنایی | جهت جریان | لیدار موبایل | زهکشی سطحی | زیرساخت های زهکشی | Semantic segmentation | Flow direction | Mobile lidar | Surface drainage | Drainage infrastructure |
مقاله انگلیسی |
52 |
General Mixed-State Quantum Data Compression With and Without Entanglement Assistance
فشرده سازی داده های کوانتومی حالت مخلوط عمومی با و بدون کمک درهم تنیدگی-2022 We consider the most general finite-dimensional
quantum mechanical information source, which is given by a
quantum system A that is correlated with a reference system R.
The task is to compress A in such a way as to reproduce the
joint source state ρAR at the decoder with asymptotically high
fidelity. This includes Schumacher’s original quantum source
coding problem of a pure state ensemble and that of a single
pure entangled state, as well as general mixed state ensembles.
Here, we determine the optimal compression rate (in qubits per
source system) in terms of the Koashi-Imoto decomposition of
the source into a classical, a quantum, and a redundant part.
The same decomposition yields the optimal rate in the presence
of unlimited entanglement between compressor and decoder, and
indeed the full region of feasible qubit-ebit rate pairs.
keywords: Quantum information | source coding | entanglement. |
مقاله انگلیسی |
53 |
Power to the people: Applying citizen science and computer vision to home mapping for rural energy access
قدرت به مردم: به کارگیری علم شهروندی و بینش رایانه در نقشهبرداری خانه برای دسترسی به انرژی روستایی-2022 To implement effective rural electricity access systems, it is fundamental to identify where potential consumers
live. Here, we test the suitability of citizen science paired with satellite imagery and computer vision to map
remote off-grid homes for electrical system design. A citizen science project called “Power to the People” was
completed on the Zooniverse platform to collect home annotations in Uganda, Kenya, and Sierra Leone. Thou-
sands of citizen scientists created a novel dataset of 578,010 home annotations with an average mapping speed of
7 km2/day. These data were post-processed with clustering to determine high-consensus home annotations. The
raw annotations achieved a recall of 93% and precision of 49%; clustering the annotations increased precision to
69%. These were used to train a Faster R-CNN object detection model, producing detections useful as a first pass
for home-level mapping with a feasible mapping rate of 42,938 km2/day. Detections achieved a precision of 67%
and recall of 36%. This research shows citizen science and computer vision to be a promising pipeline for
accelerated rural home-level mapping to enable energy system design. keywords: دانش شهروندی | بینایی کامپیوتر | دسترسی به برق | نقشه برداری روستایی | تصویربرداری ماهواره ای | سنجش از دور | Citizen science | Computer vision | Electricity access | Rural mapping | Satellite imagery | Remote sensing |
مقاله انگلیسی |
54 |
Generation of Accessible Sets in the Dynamical Modeling of Quantum Network Systems
تولید مجموعههای قابل دسترس در مدلسازی دینامیکی سیستمهای شبکه کوانتومی-2022 In this article, we consider the dynamical modeling of a class of quantum network systems consisting of
qubits, where information extraction is allowed by performing measurement on several selected qubits of the system.
For a variety of applications, a state space model is a useful
approach to modeling the system dynamics. To construct
a state space model for a quantum network system, the
major task is to find an accessible set containing all of
the operators coupled to the measurement operators. This
article focuses on the generation of a proper accessible set
for a given system and measurement scheme. We provide
analytic results on simplifying the process of generating
accessible sets for systems with a time-independent Hamiltonian. Since the order of elements in the accessible set
determines the form of state space matrices, guidance is
provided to effectively arrange the ordering of elements in
the state vector. Defining a system state according to the
accessible set, one can develop a state space model with
a special pattern inherited from the system structure. As a
demonstration, we specifically consider a typical 1-D-chain
system with several common measurements and employ
the proposed method to determine its accessible set.
Index Terms: Accessible set | dynamical modeling | quantum network system | quantum system. |
مقاله انگلیسی |
55 |
Computer vision model for estimating the mass and volume of freshly harvested Thai apple ber ( Ziziphus mauritiana L:) and its variation with storage days
مدل بینایی کامپیوتری برای تخمین جرم و حجم سیب تازه برداشت شده تایلندی (Ziziphus mauritiana L:) و تغییرات آن با روزهای نگهداری-2022 The physical properties of fruits are proportional to their mass and volume; this connection is used to determine
the fruit qualities and in designing the novel postharvest machinery. The present study aimed to forecast the
mass and volume of Thai apple ber (Ziziphus mauritiana L.) as a function of its physical properties measured using
image processing techniques at different stages of ripening (1st day, 4th day, 7th day, and 10th day). The mass
and volume models developed and analyzed the single variable regression, multilinear regressions, and mass
regression based on volume. Among these models, linear support vector machine (SVM) was found appropriate.
The experimental data analysis showed that the R2 of the linear SVM model for mass and volume of the projected
area were 0.955 and 0.965, respectively. In contrast, for the multilinear regression model, R2 values were 0.967
and 0.972, respectively. For the mass prediction model, the R2 was 0.970 based on calculated volume showing a
linear relationship. Thus, it was concluded that real-time measurement of physical properties of Thai apple ber
using an image-processing technique to estimate the mass and volume is a precise and accurate approach. keywords: بینایی کامپیوتر | پردازش تصویر | فراگیری ماشین | پسرفت | ماشین بردار پشتیبانی | Computer vision | Image processing | Machine learning | Regression | Support vector machine |
مقاله انگلیسی |
56 |
Generation of Truly Random Numbers on a Quantum Annealer
تولید اعداد واقعا تصادفی در یک آنیلر کوانتومی-2022 This study investigates how qubits of modern quantum annealers (QA) such as D-Wave can be
applied for generating truly random numbers. We show how a QA can be initialised and how the annealing
schedule can be set so that after the annealing, thousands of truly random binary numbers are measured in
parallel. Those can then be converted to uniformly distributed natural or real numbers in desired ranges,
either biased or unbiased. We discuss the observed qubits’ properties and their influence on the random
number generation and consider various physical factors that influence the performance of our generator,
i.e., digital-to-analogue quantisation errors, flux errors, temperature errors and spin bath polarisation. The
numbers generated by the proposed algorithm successfully pass various tests on randomness from the NIST
test suite. Our source code and large sets of truly random numbers will be made publicly available on our
project web page.
INDEX TERMS: Random numbers | true randomness test | superconducting flux qubits | quantum annealing | QUBO |
مقاله انگلیسی |
57 |
Human perception of color differences using computer vision system measurements of raw pork loin
درک انسان از تفاوتهای رنگی با استفاده از اندازهگیریهای سیستم بینایی کامپیوتری گوشت خوک خام-2022 In the food industry, product color plays an important role in influencing consumer choices. Yet, there remains
little research on the human ability to perceive differences in product color; therefore, preference testing is
subjective rather than based on quantitative colors. Using a de-centralized computer-aided systematic discrim-
ination testing method, we ascertain consumers’ ability to discern between systematically varied colors. As a case
study, the colors represent the color variability of fresh pork as measured by a computer vision system. Our
results indicate that a total color difference (ΔE) of approximately 1 is discriminable by consumers. Furthermore,
we ascertain that a change in color along the b*-axis (yellowness) in CIELAB color space is most discernable,
followed by the a*-axis (redness) and then the L*-axis (lightness). As developed, our web-based discrimination
testing approach allows for large scale evaluation of human color perception, while these quantitative findings
on meat color discrimination are of value for future research on consumer preferences of meat color and beyond. keywords: تست تبعیض | تست مثلث | ترجیح رنگ | ظاهر غذا | رنگ گوشت | Discrimination testing | Triange test | Color preference | Food appearance | Meat color |
مقاله انگلیسی |
58 |
Graph Kernels Encoding Features of All Subgraphs by Quantum Superposition
ویژگی های رمزگزاری هسته های گراف زیرگراف ها با برهم نهی کوانتومی-2022 Graph kernels are often used in bioinformatics and
network applications to measure the similarity between graphs;
therefore, they may be used to construct efficient graph classifiers.
Many graph kernels have been developed thus far, but to the
best of our knowledge there is no existing graph kernel that
uses some features explicitly extracted from all subgraphs to
measure similarity. We propose a novel graph kernel that applies
a quantum computer to measure the similarity obtained from all
subgraphs by fully exploiting the power of quantum superposition
to encode every subgraph into a feature of particular form. For
the construction of the quantum kernel, we develop an efficient
protocol that clears the index information of the subgraphs
encoded in the quantum state. We also prove that the quantum
computer requires less query complexity to construct the feature
vector than the classical sampler used to approximate the same
vector. A detailed numerical simulation of a bioinformatics
problem is presented to demonstrate that, in many cases, the
proposed quantum kernel achieves better classification accuracy
than existing graph kernels.
Index Terms: Quantum computing | machine learning | bioinfomatics. |
مقاله انگلیسی |
59 |
Pork primal cuts recognition method via computer vision
روش تشخیص برش های اولیه گوشت خوک از طریق بینایی کامپیوتری-2022 Pork accounts for more than 33% of global meat consumption and dominates meat consumption in China. With
the improvement of peoples quality of life, people pay more and more attention to the quality of pork. There are
many factors that affect the quality of pork, and the cutting position of pork is also one of them. The quality of
different pork primal cuts varies greatly. Aiming at the difficulty of distinguishing pork primal cuts, this study
proposes a computer vision-based method to identify different pork primal cuts, using images of four different
pork primal cuts (ham, loin, belly, and neck) as the experimental data, the results show that the method proposed
in this paper can identify the original cuts of pork well. It also proves that computer vision technology has the
potential to help people identify pork cuts. keywords: برش های اولیه گوشت خوک | شناسایی برش گوشت خوک | بینایی کامپیوتر | تشخیص برش های اولیه | Pork primal cuts | Identifying pork cut | Computer vision | Primal cuts recognition |
مقاله انگلیسی |
60 |
The application of computer vision systems in meat science and industry – A review
کاربرد سیستم های بینایی کامپیوتری در علم و صنعت گوشت – مروری-2022 Computer vision systems (CVS) are applied to macro- and microscopic digital photographs captured using digital
cameras, ultrasound scanners, computer tomography, and wide-angle imaging cameras. Diverse image acquisi-
tion devices make it technically feasible to obtain information about both the external features and internal
structures of targeted objects. Attributes measured in CVS can be used to evaluate meat quality. CVS are also used
in research related to assessing the composition of animal carcasses, which might help determine the impact of
cross-breeding or rearing systems on the quality of meat. The results obtained by the CVS technique also
contribute to assessing the impact of technological treatments on the quality of raw and cooked meat. CVS have
many positive attributes including objectivity, non-invasiveness, speed, and low cost of analysis and systems are
under constant development an improvement. The present review covers computer vision system techniques,
stages of measurements, and possibilities for using these to assess carcass and meat quality. keywords: سیستم بینایی کامپیوتری | گوشت | محصولات گوشتی | لاشه | Computer vision system | Meat | Meat products | Carcass |
مقاله انگلیسی |