surmount
发表于 2025-3-25 05:35:36
Victor A. Kovtunenko and deficits in cognitive functions. Recently, we introduced the instantaneous phase difference between electroencephalography (EEG) signals (called the dynamical phase synchronization (DPS) approach) and succeeded in detecting moment-to-moment dFC dynamics. In this approach, neural interactions in
使厌恶
发表于 2025-3-25 11:26:01
Hideyuki Azegami) Handwritten address is often of free styles and of high variations, resulting in inevitable segmentation errors. (2) The number of Chinese characters is large, leading low recognition rate for single Chinese characters. (3) Chinese address is usually irregular, i.e., different persons may write th
消息灵通
发表于 2025-3-25 15:29:35
Kohji Ohtsukaunning memory and computing resources hinder the deployment on resource-limited devices. In this paper, we propose an effective method to dynamically enhance the sparsity on channel-level. To this end, we introduce dynamic sparsity coefficient (DSC) to balance model training and sparse training as w
懦夫
发表于 2025-3-25 18:41:54
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冲突
发表于 2025-3-25 22:20:48
t such vulnerabilities in deep networks. These methods focus on attacking and retraining deep networks with adversarial examples to do either feature manipulation or label manipulation or both. In this paper, we propose a new adversarial learning algorithm for finding adversarial manipulations to de
颂扬国家
发表于 2025-3-26 04:04:31
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instate
发表于 2025-3-26 05:11:52
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南极
发表于 2025-3-26 09:02:25
Daijun Jiang,Yikan Liu,Masahiro Yamamotobrains. Recently, there have been several approaches to explain the action generation within the predictive brain hypotheses: the brain predicts the animal’s own action, which the animal realizes to fulfill the prediction. In this study, we suggest a predictive brain models to produce the goal direc
固执点好
发表于 2025-3-26 15:20:48
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filicide
发表于 2025-3-26 20:02:14
Yasuhide Fukumoto,Valery L. Okulov,David H. Woodion for fine-grained object retrieval (FGOR). However, existing methods construct the embedding based solely on features extracted by the last layer of CNN, neglecting the potential benefits of leveraging features from other layers. Based on the fact that features extracted by different layers of CN