micronutrients
发表于 2025-3-25 06:57:56
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insert
发表于 2025-3-25 09:47:05
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COMA
发表于 2025-3-25 13:41:33
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cathartic
发表于 2025-3-25 17:26:19
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PRE
发表于 2025-3-25 22:03:43
https://doi.org/10.1007/978-3-662-65598-6ies of insect pests. It incorporates well over 34,089 photos that are divided into 50 categories and have a naturally long-tailed distribution. A comparison of the performance of ViT is done with the ResNet model on the same data and it is found that the ViT model performs better than the ResNet model.
皮萨
发表于 2025-3-26 03:39:34
Bernhard Badura,Antje Ducki,Helmut Schröder train cutting-edge Deep Learning Algorithms for shadow detection. Experimental results using various Deep learning Object Detection (DLOD) models and performance metrics demonstrate promising effectiveness. Although this approach is limited to detecting attacks from certain angles, it is a valuable addition to existing bird detection methods.
BAIT
发表于 2025-3-26 07:33:39
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synovitis
发表于 2025-3-26 11:34:35
An Improved Deep Learning Model Implementation for Pest Species Detection,ies of insect pests. It incorporates well over 34,089 photos that are divided into 50 categories and have a naturally long-tailed distribution. A comparison of the performance of ViT is done with the ResNet model on the same data and it is found that the ViT model performs better than the ResNet model.
Inflated
发表于 2025-3-26 13:19:31
Real-Time Birds Shadow Detection for Autonomous UAVs, train cutting-edge Deep Learning Algorithms for shadow detection. Experimental results using various Deep learning Object Detection (DLOD) models and performance metrics demonstrate promising effectiveness. Although this approach is limited to detecting attacks from certain angles, it is a valuable addition to existing bird detection methods.
Interlocking
发表于 2025-3-26 17:12:35
,Knowledge Graph for Fraud Detection: Case of Fraudulent Transactions Detection in Kenyan SACCOs,iveness of the approach is evaluated using real-world SACCO transaction data and shows that it can detect potential fraud in real-time or near real-time thereby saving funds that would have been lost.