The project proposes an Examination Feedback System utilizing machine learning to automate the evaluation of subjective answers in educational assessments. The system will analyze student responses and classify them u...
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Fingerprint identification plays a crucial role in crime detection, but manual analysis is time-consuming and error-prone. This research aims to develop an automated system for accurate and efficient fingerprint match...
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Diabetic retinopathy(DR),a long-term complication of diabetes,is notoriously hard to detect in its early stages due to the fact that it only shows a subset of *** diagnostic procedures for DR now include optical coher...
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Diabetic retinopathy(DR),a long-term complication of diabetes,is notoriously hard to detect in its early stages due to the fact that it only shows a subset of *** diagnostic procedures for DR now include optical coherence tomography and digital fundus *** digital fundus images alone could provide a reliable diagnosis,then eliminating the costly optical coherence tomography would be beneficial for all parties *** and their patients will find this *** deep convolutional neural networks(DCNNs),we provide a novel approach to this *** approach deviates from standard DCNN methods by exchanging typical max-pooling layers with fractional max-pooling *** order to collect more subtle information for categorization,two such DCNNs,each with a different number of layers,are *** establish these limits,we use DCNNs and features extracted from picture metadata to train a support vector machine *** our experiments,we used information from Kaggle’s open DR detection *** fed our model 34,124 training images,1,000 validation examples,and 53,572 test images to train and test *** of the five classes in the proposed DR classifier corresponds to one of the steps in the DR process and is given a numeric value between 0 and *** results show a higher identification rate(86.17%)than those found in the existing literature,indicating the suggested strategy may be *** have jointly developed an algorithm for machine learning and accompanying software,and we’ve named it deep *** of the fundus acquired by the typical person using a portable ophthalmoscope may be instantly analyzed using our *** technology might be used for self-diagnosis,at-home care,and telemedicine.
The revolutionary effects of quantum computing on security procedures for networks and cryptographic protocols are the focus of this study. Our research shows that conventional cryptographic algorithms are susceptible...
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This study aims to introduce a cutting-edge method for weave defect detection using Artificial intelligence (AI) and computer vision (CV) technologies. By employing a Convolutional neural network (CNN) trained on a co...
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Multi-object tracking(MOT)has seen rapid improvements in recent ***,frequent occlusion remains a significant challenge in MOT,as it can cause targets to become smaller or disappear entirely,resulting in lowquality tar...
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Multi-object tracking(MOT)has seen rapid improvements in recent ***,frequent occlusion remains a significant challenge in MOT,as it can cause targets to become smaller or disappear entirely,resulting in lowquality targets,leading to trajectory interruptions and reduced tracking *** from some existing methods,which discarded the low-quality targets or ignored low-quality target ***,with a lowquality association strategy(LQA),is proposed to pay more attention to low-quality *** the association scheme of LQTTrack,firstly,multi-scale feature fusion of FPN(MSFF-FPN)is utilized to enrich the feature information and assist in subsequent data ***,the normalized Wasserstein distance(NWD)is integrated to replace the original Inter over Union(IoU),thus overcoming the limitations of the traditional IoUbased methods that are sensitive to low-quality targets with small sizes and enhancing the robustness of low-quality target ***,the third association stage is proposed to improve the matching between the current frame’s low-quality targets and previously interrupted trajectories from earlier frames to reduce the problem of track fragmentation or error tracking,thereby increasing the association success rate and improving overall multi-object tracking *** experimental results demonstrate the competitive performance of LQTTrack on benchmark datasets(MOT17,MOT20,and DanceTrack).
Quantum computing has been widely applied in various fields, such as quantum physics simulations, quantum machine learning, and big data analysis. However, in the domains of data-driven paradigms, ensuring databases p...
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The COVID-19 pandemic poses a global health challenge. The World Health Organization states that face masks are proven to be effective, especially in public areas. Real-time monitoring of face masks is challenging and...
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High-throughput computing(HTC) is a computing paradigm that aims to accomplish jobs by easily breaking them into smaller,independent ***,it requires a large amount of computing power for a long *** existing HTC framew...
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High-throughput computing(HTC) is a computing paradigm that aims to accomplish jobs by easily breaking them into smaller,independent ***,it requires a large amount of computing power for a long *** existing HTC frameworks are job-oriented without support for coscheduling with hardware architecture and task-level ***,most of the frameworks reach a limited scale,and their usability needs further ***,we present HTDcr,a job execution framework for the HTC on *** study aims to improve the throughput,task dispatching,and usability of the *** detail,the throughput optimizations include a sophisticated designed task management system,a hierarchical scheduler,and the co-optimization of the task-scheduling strategy with the application and hardware *** optimizations for usability include a programable execution workflow,mechanisms for more robust and reliable service qualities,and a fine-grained resource allocation system for the colocation of multiple *** to our evaluations,HTDcr can achieve outstanding scalability and high throughput on large-scale clusters for the HTC *** evaluate HTDcr with several microbenchmarks and real-world applications on Tianhe-2 and Sunway TaihuLight to demonstrate its effects on existing design *** instance,the task scheduling for two real-world applications integrated with the application and hardware characteristics achieves 1.7× and 1.9× speedups over the basic task-scheduling strategy.
Implemented Image captioning is becoming a need. Deep neural network models enable integrated applications to generate and caption images. Image captioning describes an image. It requires identifying an image's ma...
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