莎草 发表于 2025-3-26 22:58:39
Variabilität – Ohne Vielfalt keine Evolutionlize question information, and the joint prediction module we designed can fully integrate the performance of the two branches. Extensive experimental results demonstrate that our proposed method outperforms the current state-of-the-art methods in terms of performance.包租车船 发表于 2025-3-27 01:25:54
http://reply.papertrans.cn/17/1672/167150/167150_32.png最小 发表于 2025-3-27 05:47:24
https://doi.org/10.1007/978-3-642-92192-6rsor neurons before activation occurs. Each neuron transmits its path and knowledge to its successor through waves while objective neurons calculate final recognition based on received waves and output optimal solutions. Evaluation using four public datasets shows that TSWNN outperforms A*, Dijkstra, Label, and TDNN.MODE 发表于 2025-3-27 13:18:46
http://reply.papertrans.cn/17/1672/167150/167150_34.png茁壮成长 发表于 2025-3-27 14:23:08
http://reply.papertrans.cn/17/1672/167150/167150_35.png微尘 发表于 2025-3-27 18:30:25
SCAI: A Spectral Data Classification Framework with Adaptive Inference for Rapid and Portable Identi on important information. To our knowledge, this paper is the first attempt to leverage adaptive inference for liquor identification. The experimental results show that our method can achieve higher identification performance (+6%−+ 13% under the same budget) with less computational budget (1/6 for the same performance) than existing methods.争吵 发表于 2025-3-28 01:10:50
http://reply.papertrans.cn/17/1672/167150/167150_37.png垄断 发表于 2025-3-28 06:04:02
http://reply.papertrans.cn/17/1672/167150/167150_38.pnghermitage 发表于 2025-3-28 08:12:54
Trust Evaluation with Deep Learning in Online Social Networks: A State-of-the-Art Reviewcomplexity as network size expands, and imbalanced datasets typically lead to reduced model accuracy and generalization. Lastly, it presents several promising avenues for future research in the field.ALLEY 发表于 2025-3-28 10:28:07
CNN-SENet: A Convolutional Neural Network Model for Audio Snoring Detection Based on Channel Attenti focus on multidimensional feature weights, ensuring high robustness and excellent analysis efficiency in the face of environmental noise interference. Experimental results validate the effectiveness of the proposed model, achieving 100% snoring recognition accuracy in noiseless environments and mai