標(biāo)題: Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2023; 32nd International C Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay Confe [打印本頁] 作者: ISSUE 時間: 2025-3-21 18:17
書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023影響因子(影響力)
書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023影響因子(影響力)學(xué)科排名
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書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023被引頻次
書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023被引頻次學(xué)科排名
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書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023讀者反饋
書目名稱Artificial Neural Networks and Machine Learning – ICANN 2023讀者反饋學(xué)科排名
作者: Geyser 時間: 2025-3-22 00:08 作者: duplicate 時間: 2025-3-22 04:20
Zug-, Druck- und Scherfestigkeit,erformed person identification tasks using ten sub-datasets sampled from a large-scale CBP dataset. Our proposed method achieved higher recognition accuracy than other relevant methods in spite of its relatively low computational cost on segment-by-segment and aggregated recognition tasks, respectively.作者: 無目標(biāo) 時間: 2025-3-22 08:38 作者: 積習(xí)已深 時間: 2025-3-22 09:39
,An Echo State Network-Based Method for?Identity Recognition with?Continuous Blood Pressure Data,erformed person identification tasks using ten sub-datasets sampled from a large-scale CBP dataset. Our proposed method achieved higher recognition accuracy than other relevant methods in spite of its relatively low computational cost on segment-by-segment and aggregated recognition tasks, respectively.作者: CRAMP 時間: 2025-3-22 14:58 作者: MORT 時間: 2025-3-22 20:16 作者: 懸掛 時間: 2025-3-22 23:34 作者: 舔食 時間: 2025-3-23 02:20
https://doi.org/10.1007/978-3-662-11735-4olecular Structure-based Double-Central Drug-Drug Interaction prediction(MSDC-DDI). MSDC-DDI utilizes a double-central encoder and a cross-dependent schema to generate the representations of the drugs. MSDC-DDI made effective and accurate predictions, which achieved up to more than 99% in DDI prediction.作者: debunk 時間: 2025-3-23 07:02 作者: 滑稽 時間: 2025-3-23 11:01 作者: agitate 時間: 2025-3-23 14:14
,Analysis and?Interpretation of?ECG Time Series Through Convolutional Neural Networks in?Brugada Synexperimental assessments we use an original dataset of 306 ECGs collected from several clinical centers within the BrAID (Brugada syndrome and Artificial Intelligence applications to Diagnosis) project.作者: 我吃花盤旋 時間: 2025-3-23 19:18
Molecular Structure-Based Double-Central Drug-Drug Interaction Prediction,olecular Structure-based Double-Central Drug-Drug Interaction prediction(MSDC-DDI). MSDC-DDI utilizes a double-central encoder and a cross-dependent schema to generate the representations of the drugs. MSDC-DDI made effective and accurate predictions, which achieved up to more than 99% in DDI prediction.作者: 閑聊 時間: 2025-3-24 00:20 作者: 可互換 時間: 2025-3-24 06:26
The Optimization and Parallelization of Two-Dimensional Zigzag Scanning on the Matrix,lts show that our proposed schemes perform well with large scales of matrices. Moreover, the design of parallel programming based on our proposed scheme has been given. Finally, we have discussed the efficiency of parallelization. The speedup we get is from 3.413 to 3.996, which is stably growth with the scales of matrices.作者: Precursor 時間: 2025-3-24 09:43
Risk Stratification of Malignant Melanoma Using Neural Networks,ine learning methods, alterations of scanner-specific properties such as brightness, contrast or sharpness can have strong (negative) effects on the quality of the prediction methods, two ways to overcome this domain gap are discussed in this paper.作者: anniversary 時間: 2025-3-24 12:51
0302-9743 n brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.??.978-3-031-44215-5978-3-031-44216-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: hysterectomy 時間: 2025-3-24 17:25
0302-9743 ne Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023..The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks i作者: cunning 時間: 2025-3-24 22:52
Artificial Neural Networks and Machine Learning – ICANN 2023978-3-031-44216-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 昏睡中 時間: 2025-3-24 23:49 作者: 合群 時間: 2025-3-25 05:32 作者: Proponent 時間: 2025-3-25 10:49 作者: AVANT 時間: 2025-3-25 13:16
https://doi.org/10.1007/978-3-7091-9977-0s therein. However, accurate brain tumor diagnosis is challenging because: 1) data is corrupted with noise, 2) data is relatively scarce, 3) patient representation is unbalanced, i.e., the number of spectra per patient varies, 4) visual inspection of the MRS data suffers from large inter-rater varia作者: Delude 時間: 2025-3-25 19:49 作者: FLUSH 時間: 2025-3-25 20:09
Zug-, Druck- und Scherfestigkeit,S), a rare heart rhythm disease, from the electrocardiogram (ECG) time series. First, the model is assessed on the ECG classification of type-1 BrS. Then, we define a method to interpret the BrS prediction through Gradient-weighted Class Activation Mapping (Grad-CAM) applied to continuous time serie作者: 柔聲地說 時間: 2025-3-26 04:07 作者: 混亂生活 時間: 2025-3-26 06:38
Hartmut Bossel,Walter Heil,Alfred Puckon. As an ophthalmic emergency, BK and FK need to be treated correctly as soon as possible to prevent irrecoverable damage to vision, but the early correct diagnosis between them is challenging. Some research have shown that even trained ophthalmologists have less than 80% accuracy in correctly diag作者: 愛國者 時間: 2025-3-26 10:25
,Beispiel für die Anwendung der Ergebnisse,ival rates. Because the bilateral breasts of the same patient are similar and symmetrical, information fusion of bilateral mammogram images is advantageous in improving the detection rate of masses. However, existing mass detection methods use pixel-level corresponding feature fusion methods, which 作者: Aggregate 時間: 2025-3-26 14:59
Zufallsschwingungen linearer Systeme, important for both diagnosis and treatment of cardiac diseases. Existing automatic segmentation methods for cardiac MRI are based on U-shaped network structure introducing global pooling, attention and etc. operations to extract more effective features. These approaches, however, suffer from a mism作者: 跑過 時間: 2025-3-26 19:35 作者: 天真 時間: 2025-3-26 21:34 作者: 果核 時間: 2025-3-27 03:43 作者: Vldl379 時間: 2025-3-27 09:12
https://doi.org/10.1007/978-3-662-11735-4ntial for medical health. Most of the existing methods rely heavily on manually engineered domain knowledge, therefore, lack generalization and are inefficient. Drugs with similar molecular structures have similar chemical properties. The molecular structures of drugs can be obtained easily and the 作者: 古董 時間: 2025-3-27 11:55 作者: 膽小鬼 時間: 2025-3-27 15:19
https://doi.org/10.1007/978-3-662-11735-4f up to 0.78 without additional clinical information. Furthermore, the importance of the domain gap between two different image sources is considered, as it is important to create usability independent of hardware components such as the high-resolution scanner used. Since for the application of mach作者: 背心 時間: 2025-3-27 21:50 作者: 無效 時間: 2025-3-28 01:07
https://doi.org/10.1007/978-3-662-07208-0ous quantities of data need to be crunched in order to get the valuable parts and discard redundant ones. For those data represented as two-dimensional digital matrix, two alternative schemes by scanning the elements of the matrix in zigzag route have been proposed. Fixed-point mode and navigation m作者: EPT 時間: 2025-3-28 05:36 作者: 瘙癢 時間: 2025-3-28 09:01
,Die elastizit?tstheoretischen Grundlagen, of manual pixel-level annotations. Existing methods relying on class activation map (CAM) to localize target objects suffer from two problems. First, most CAM-based models adopt convolutional neural networks, which cannot model the long-range dependencies of dispersed tissues. Second, CAM tends to 作者: 信徒 時間: 2025-3-28 10:48 作者: 異端 時間: 2025-3-28 15:59 作者: defendant 時間: 2025-3-28 21:21 作者: 體貼 時間: 2025-3-28 22:54 作者: 剝皮 時間: 2025-3-29 04:02 作者: 音樂會 時間: 2025-3-29 11:00 作者: Glaci冰 時間: 2025-3-29 11:40
,Clinical Pixel Feature Recalibration Module for?Ophthalmic Image Classification,l ability of CNNs. Our CPF is easily inserted into existing CNNs with negligible overhead. We conduct comprehensive experiments on two publicly available ophthalmic image datasets and CIFAR datasets, and the results show the superiority and generation ability of CPF over advanced attention methods. 作者: 相信 時間: 2025-3-29 16:48 作者: saturated-fat 時間: 2025-3-29 19:42
IESBU-Net: A Lightweight Skin Lesion Segmentation UNet with Inner-Module Extension and Skip-Connecthe process of feature fusion between encoder and decoder, which is used to smooth the semantic gap between encoder and decoder caused by skip-connection. We evaluated the proposed model on the ISIC 2017 and ISIC 2018 datasets. The experimental results show that the model achieves a good balance betw作者: 共同生活 時間: 2025-3-30 00:39 作者: LAP 時間: 2025-3-30 06:43
,Tooth Segmentation from?Cone-Beam CT Images Through Boundary Refinement,d to conduct two different works in parallel. One is to directly predict the individual tooth segmentation while the other is to generate an offset map for the refinement. Besides, in order to improve the accuracy of tooth boundary segmentation, a boundary-aware loss is also applied in our method. C作者: white-matter 時間: 2025-3-30 09:02
,Transformer Based Prototype Learning for?Weakly-Supervised Histopathology Tissue Semantic Segmentatto obtain more complete localization maps. Additionally, we introduce a self-refinement mechanism to dampen the falsely activated regions in the initial localization map. Extensive experiments on two histopathology datasets demonstrate that our proposed model achieves the state-of-the-art performanc作者: archetype 時間: 2025-3-30 15:34 作者: Density 時間: 2025-3-30 19:06
,A Graph Convolutional Siamese Network for?the?Assessment and?Recognition of?Physical Rehabilitation model reaches state-of-the-art performance on action classification and outperforms the Dynamic Time Warping algorithm and hidden Markov model method by a large margin in terms of assessment accuracy.作者: SOBER 時間: 2025-3-30 23:18 作者: HOWL 時間: 2025-3-31 04:39
Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay作者: 放肆的我 時間: 2025-3-31 07:06
https://doi.org/10.1007/978-3-7091-9977-0 of min-, max-, and average-pooling of the features, and 2) a self-attention mechanism. We evaluate the proposed method on multiple neural network architectures in a five-fold leave-patient-out cross-validation scheme and also against human experts on a withheld data set. We find that classification作者: dialect 時間: 2025-3-31 10:30 作者: Modify 時間: 2025-3-31 14:56
Hartmut Bossel,Walter Heil,Alfred Puck87.20%, 83.12%, 0.85 and 0.85 respectively, which has achieved the best effect compared with other classification methods. Furthermore, visualization technique Grad-CAM++ is used to provide interpretability for the validity of our model.作者: Expurgate 時間: 2025-3-31 17:31
Zufallsschwingungen linearer Systeme,e dilated convolutions. In order to improve the ability to learn the precise boundary of the objects, a gated boundary-aware branch is introduced and utilized to concentrate on the object border region. The effectiveness and robustness of the network are confirmed by evaluating this method on the AC作者: 粘土 時間: 2025-3-31 23:28 作者: 運動吧 時間: 2025-4-1 03:39
Siegfried Schwaigerer,Gerd Mühlenbecks that are not contained in the predefined vocabulary. Furthermore, we propose a local correlation detecting (LCD) task and fine-tune the augmented Transformers in a multi-task fashion. Extensive experiments on two public datasets show that the augmented Transformers significantly outperform their b作者: 得意人 時間: 2025-4-1 09:06
https://doi.org/10.1007/978-3-642-59090-0he process of feature fusion between encoder and decoder, which is used to smooth the semantic gap between encoder and decoder caused by skip-connection. We evaluated the proposed model on the ISIC 2017 and ISIC 2018 datasets. The experimental results show that the model achieves a good balance betw作者: 憤怒事實 時間: 2025-4-1 12:28
https://doi.org/10.1007/978-3-662-07208-0mportant features of each lung field..Compared to state-of-the-art baseline models (DenseNet, Mask R-CNN), symmetry-aware training can improve the AUROC score by up to 10%. Furthermore, the findings indicate that, by integrating the bilateral symmetry of the lung field, the interpretability of the m作者: mortuary 時間: 2025-4-1 17:22
,Die elastizit?tstheoretischen Grundlagen,d to conduct two different works in parallel. One is to directly predict the individual tooth segmentation while the other is to generate an offset map for the refinement. Besides, in order to improve the accuracy of tooth boundary segmentation, a boundary-aware loss is also applied in our method. C作者: 失望昨天 時間: 2025-4-1 20:22
,Die elastizit?tstheoretischen Grundlagen,to obtain more complete localization maps. Additionally, we introduce a self-refinement mechanism to dampen the falsely activated regions in the initial localization map. Extensive experiments on two histopathology datasets demonstrate that our proposed model achieves the state-of-the-art performanc
