Titlebook: Belief Functions: Theory and Applications; 8th International Co Yaxin Bi,Anne-Laure Jousselme,Thierry Denoeux Conference proceedings 2024 T

桌前不可入

書目名稱Belief Functions: Theory and Applications影響因子(影響力)




書目名稱Belief Functions: Theory and Applications影響因子(影響力)學(xué)科排名




書目名稱Belief Functions: Theory and Applications網(wǎng)絡(luò)公開度




書目名稱Belief Functions: Theory and Applications網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Belief Functions: Theory and Applications被引頻次




書目名稱Belief Functions: Theory and Applications被引頻次學(xué)科排名




書目名稱Belief Functions: Theory and Applications年度引用




書目名稱Belief Functions: Theory and Applications年度引用學(xué)科排名




書目名稱Belief Functions: Theory and Applications讀者反饋




書目名稱Belief Functions: Theory and Applications讀者反饋學(xué)科排名

乏味

討厭

ANA

Conflict Management in?a?Distance to?Prototype-Based Evidential Deep LearningThe experimental results are obtained using a lidar-camera cross-fusion architecture with evidential formulation based on Dempster-Shafer’s theory. The model is investigated on a road detection task and it uses the KITTI dataset.

affluent

https://doi.org/10.1007/978-3-540-44760-3kes place currently. For voluminous datasets, users can also adjust the update frequency according to their specific requirements. Compared to state-of-the-art (SoTA) stream clustering algorithms, IEC demonstrates better clustering accuracy and comparable runtime across four benchmark datasets. IEC

Conquest

共同時(shí)代

1 Deformation behaviour of steel,pproach presented in the work [.]. Hence, this enables us to detect hallucinations by evaluating the conflict among evidence. Preliminary experiments were conducted on a state-of-the-art LVLM, mPLUG-Owl2. Results show that our approach exhibits an enhancement over baseline methods, particularly in c

LATER

zonules

An Evidential Time-to-Event Prediction Model Based on?Gaussian Random Fuzzy Numbersdel is fit by minimizing a generalized negative log-likelihood function that accounts for both normal and censored data. Comparative experiments on two real-world datasets demonstrate the very good performance of our model as compared to the state-of-the-art.

BAIL