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Titlebook: Intelligent Computing and Innovation on Data Science; Proceedings of ICTID Sheng-Lung Peng,Sun-Yuan Hsieh,Balaganesh Duraisam Conference pr

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發(fā)表于 2025-3-23 11:31:08 | 只看該作者
Recent Trends in Potential Security Solutions for SD-WAN: A Systematic Review,he performance of the monitoring schemes and data transmission across the network. The innovations in the SD-WAN have embarked due to the advancement in network applications. Various operational scenarios and applications have necessitated long-range data transmission, whereas the transmission netwo
12#
發(fā)表于 2025-3-23 16:52:56 | 只看該作者
SVM- and K-NN-Based Paddy Plant Insects Recognition,. The worth and magnitude of farming yields are pretentious through ecological limits like rainfall, temperature and climate parameter, away from managing person beings. One more important organic parameter that influences yields harvest is the insects bytes that can be controlled to better crop yie
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發(fā)表于 2025-3-23 18:46:40 | 只看該作者
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發(fā)表于 2025-3-24 01:12:58 | 只看該作者
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發(fā)表于 2025-3-24 04:35:16 | 只看該作者
Deep Learning in Image Signal Processing for Minimal Method by Using Kernel DBN,energy efficient. However, their adverse impact was severely underestimated by precision. The conventional vision pipeline undermines the accuracy of standard post-ISP datasets-trained machine learning algorithms. For example, in a car detection case, the off-the-shelf Faster RCNN algorithm’s detect
16#
發(fā)表于 2025-3-24 07:47:03 | 只看該作者
Bone Age Measurement-Based on Dental Radiography, Employing a New Model,ng the radiographic image of one’s wrist or dentition with an existing uniform map, which contains a series of age-recognized images at any point of its development. Manual methods are based on the analysis of specific areas of hand bone images or dental structures. Both approaches are vulnerable to
17#
發(fā)表于 2025-3-24 13:11:16 | 只看該作者
18#
發(fā)表于 2025-3-24 15:21:40 | 只看該作者
Implementation and Performance Analysis of Various Models of PCNN for Medical Image Segmentation, The pulse-coupled neural network (PCNN) models can segment the objects in an image. This paper analyzes the suitability of PCNN models for high-performance biomedical image segmentation. In this research work, three different PCNN models have used to evaluate the performance of classifying the medi
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發(fā)表于 2025-3-24 19:47:50 | 只看該作者
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發(fā)表于 2025-3-25 00:27:23 | 只看該作者
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