Efficient Algorithms for E-Healthcare to Solve Multiobject Fuse Detection Problem
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Post-publication record
- Nature
- Retraction
- Reason
- Concerns/Issues about Data;Concerns/Issues about Results and/or Conclusions;Concerns/Issues about Referencing/Attributions;Concerns/Issues about Peer Review;Investigation by Journal/Publisher;Investigation by Third Party;Paper Mill;Computer-Aided Content or Computer-Generated Content;Unreliable Results and/or Conclusions;
- Date
- 8/30/2023 0:00
- Flagged by OpenAlex?
- Yes
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Abstract
Object detection plays a vital role in the fields of computer vision, machine learning, and artificial intelligence applications (such as FUSE-AI (E-healthcare MRI scan), face detection, people counting, and vehicle detection) to identify good and defective food products. In the field of artificial intelligence, target detection has been at its peak, but when it comes to detecting multiple targets in a single image or video file, there are indeed challenges. This article focuses on the improved K-nearest neighbor (MK-NN) algorithm for electronic medical care to realize intelligent medical services and applications. We introduced modifications to improve the efficiency of MK-NN, and a comparative analysis was performed to determine the best fuse target detection algorithm based on robustness, accuracy, and computational time. The comparative analysis is performed using four algorithms, namely, MK-NN, traditional K-NN, convolutional neural network, and backpropagation. Experimental results show that the improved K-NN algorithm is the best model in terms of robustness, accuracy, and computational time.
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The record
- Venue
- Journal of Healthcare Engineering
- Topic
- Advanced Neural Network Applications
- Field
- Computer Science
- Canadian institutions
- Université de Moncton
- Funders
- Taif University
- Keywords
- Robustness (evolution)Fuse (electrical)Computer scienceConvolutional neural networkArtificial intelligenceObject detectionComputational intelligenceArtificial neural networkAlgorithmMachine learningBackpropagationFace detectionField (mathematics)Pattern recognition (psychology)Facial recognition system
- Has abstract in OpenAlex
- yes