semiskilled
发表于 2025-4-1 02:36:32
Deep Learning-Based Classification of Conference Paper Reviews: Accept or Reject?, framework. Next, to explain the results produced by deep learning (DL) models, Local Interpretable Model-Agnostic Explanations (LIME), SHapley Additive exPlanations (SHAP), and Anchor Explainer have been applied. Among the applied DL techniques, the Bi-GRU-LSTM-CNN model attained the highest accura
Orgasm
发表于 2025-4-1 06:07:31
http://reply.papertrans.cn/48/4763/476207/476207_62.png
拔出
发表于 2025-4-1 13:02:14
Deep-Net: Brain Lesion Segmentation with 3D CNN and Residual Connections,tions. Through a comparative analysis, we illustrate the effectiveness of integrating residual connections into the first layer of our approach. Our approach has undergone testing using the BRATS 2015 training database, demonstrating robust performance despite the simplicity of the pipeline.
Cholecystokinin
发表于 2025-4-1 14:30:39
,Brood Parasitism Identification Using a Deep Learning Model with Mish Activation Function,emely accurate parasitic egg identification. Actually, our model has been evaluated on two data sets: the first is for the GRW egg and Cuckoo egg, and the second is for the RW and Cuckoo egg, and it has an accuracy of 94.7% and 90.9%, respectively.
报复
发表于 2025-4-1 19:08:03
2367-3370 hors from 64 countries. This book offers a valuable reference guide for all industrial specialists, scientists, academicians, researchers, students, and practitioners in the field of artificial intelligence and industrial applications..978-3-031-64775-8978-3-031-64776-5Series ISSN 2367-3370 Series E-ISSN 2367-3389
mitten
发表于 2025-4-2 01:22:01
http://reply.papertrans.cn/48/4763/476207/476207_66.png
Surgeon
发表于 2025-4-2 04:05:12
http://reply.papertrans.cn/48/4763/476207/476207_67.png
不安
发表于 2025-4-2 07:00:25
Somayeh Koohborfardhaghighi,Gert De Geyter,Evan Kaliner
埋葬
发表于 2025-4-2 12:30:36
http://reply.papertrans.cn/48/4763/476207/476207_69.png
膝盖
发表于 2025-4-2 15:51:03
Leonardo Goliatt,Priscila V. S. Z. Capriles,Gabriele Cesar Iwashima,João Paulo Scoralick