The substantial rise in Oman's load in recent years prompted researchers to investigate ways to reduce the construction of new power plants. Reducing the electricity consumption during the peak hours will provide ...
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作者：
Hyeon, SoojeongASRI
Department of Electrical and Computer Engineering Seoul National University Korea Republic of
This paper presents a distributed estimation scheme for determining the geometric center of multiple targets by a group of agents in 2-dimensional space. These agents have the knowledge of bearing measurements to a pa...
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Depression is a common and serious mental illness that affects millions of people worldwide. Early diagnosis and treatment of depression are essential to improve the quality of life of those affected. Traditional meth...
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In Natural Language Processing (NLP), textual data is foundational, yet it presents substantial challenges, especially for under-resourced languages like Bengali. The complexity and volume of Bengali textual data requ...
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The standardized 6TiSCH network offers high throughput, reliable, delay-bounded, and energy-efficient communication in Internet of Things networks. For 6TiSCH bootstrapping, 6TiSCH minimal configuration standard has b...
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Traditional voting procedures are non-remote, time-consuming, and less secure. While the voter believes their vote was submitted successfully, the authority does not provide evidence that the vote was counted and tall...
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Anumber of research papers including several review papers have reported that autonomous vehicles(AVs)consume a significant amount of power to run the onboard computers that do all the calculations needed to process a...
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Anumber of research papers including several review papers have reported that autonomous vehicles(AVs)consume a significant amount of power to run the onboard computers that do all the calculations needed to process and analyze the sig-nificant amount of *** addition,there is a substantial amount of power consumption by onboard sensors including radars,cam-eras,Lidars,etc.[1]The resulting power consumption results in range reduction in electric autonomous *** in-turn increases the emissions based on how the electricity is obtained for charging these vehicle *** the degree of automation moves up the ladder of AVs,the complexity of the overall control,management,and the associated tasks grow exponentially,and hence increasing the power *** Society of Auto-motive Engineers(SAE)defines 6 levels of driving automation ranging from Level 0(fully manual)to Level 5(fully autonomous).Level 0 is no driving automation and the driver is responsible for full control of the *** 1 is the driver assisted by a support system like adaptive cruise control or lane-changing assistance,but the driver must remain *** Level 2.
Accumulated Chest X-Ray images have widely been used in the task of automating the diagnosis of thoracic diseases. Multiple studies on using single classifiers for this task and also some studies on the fusion of clas...
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ISBN:
(纸本)9798331529710
Accumulated Chest X-Ray images have widely been used in the task of automating the diagnosis of thoracic diseases. Multiple studies on using single classifiers for this task and also some studies on the fusion of classifiers for the same purpose have been previously done and all have reached promising results. On furthering the classifier fusion approach, we have implemented a variation of methods including those used in the SynthEnsemble [1] paper on the ChestX-ray14 dataset [2], while focusing on the balance of classifier diversity and accuracy and using the same pre-trained single classifiers from SynthEnsemble as grounds for comparison. We have conducted all the same decision fusion methods, such as weighted averaging and using stochastic global optimization methods for classifier weight optimization, and have also employed new and additional methods, such as various heuristic and intelligent weight optimization methods, with regards to optimizing the number of base classifiers for reducing the computational cost and tuning the accumulated diversity of the fused network. The proposed approach, in summary, is a comparison between a brute-force based global heuristic search as a classifier weight optimizer, and genetically inspired stochastic weight optimizations added to an ordered weighted averaging fusion method, complemented with minimizing the set of base classifiers in accordance to their accuracy-diversity trade-off. Throughout this study, we use various metrics of model evaluation through all of which we have reached better or at least similar performance results while lowering the diversity of the set of chosen classifiers, reducing the number of base classifiers from six to four, and decreasing the execution time by a notable 98.7%. Even notwithstanding the improved performance of our proposed fusion methods, which is greatly dependent on the choice of base classifiers and is strictly limited to those used in [1] for accurate comparison, we can draw the
Handwrítten digil recognition remains a cumplcx challenge ín computer visión, characlcrized by diverse wriling stylcs, varying dislortivn levéis, and datase! noisc. This pnper introduces a novel mo...
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With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation *** X-ray baggage monitoring is now standard,...
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With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation *** X-ray baggage monitoring is now standard,manual screening has several limitations,including the propensity for errors,and raises concerns about passenger *** address these drawbacks,researchers have leveraged recent advances in deep learning to design threatsegmentation ***,these models require extensive training data and labour-intensive dense pixelwise annotations and are finetuned separately for each dataset to account for inter-dataset ***,this study proposes a semi-supervised contour-driven broad learning system(BLS)for X-ray baggage security threat instance segmentation referred to as *** research methodology involved enhancing representation learning and achieving faster training capability to tackle severe occlusion and class imbalance using a single training routine with limited baggage *** proposed framework was trained with minimal supervision using resource-efficient image-level labels to localize illegal items in multi-vendor baggage *** specifically,the framework generated candidate region segments from the input X-ray scans based on local intensity transition cues,effectively identifying concealed prohibited items without entire baggage *** multi-convolutional BLS exploits the rich complementary features extracted from these region segments to predict object categories,including threat and benign *** contours corresponding to the region segments predicted as threats were then utilized to yield the segmentation *** proposed C-BLX system was thoroughly evaluated on three highly imbalanced public datasets and surpassed other competitive approaches in baggage-threat segmentation,yielding 90.04%,78.92%,and 59.44%in terms of mIoU on GDXray,SIXray,and Compass-XP,***,the lim
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