標題: Titlebook: Cognitive Systems and Signal Processing; 5th International Co Fuchun Sun,Huaping Liu,Bin Fang Conference proceedings 2021 Springer Nature S [打印本頁] 作者: Mosquito 時間: 2025-3-21 16:16
書目名稱Cognitive Systems and Signal Processing影響因子(影響力)
書目名稱Cognitive Systems and Signal Processing影響因子(影響力)學科排名
書目名稱Cognitive Systems and Signal Processing網(wǎng)絡公開度
書目名稱Cognitive Systems and Signal Processing網(wǎng)絡公開度學科排名
書目名稱Cognitive Systems and Signal Processing被引頻次
書目名稱Cognitive Systems and Signal Processing被引頻次學科排名
書目名稱Cognitive Systems and Signal Processing年度引用
書目名稱Cognitive Systems and Signal Processing年度引用學科排名
書目名稱Cognitive Systems and Signal Processing讀者反饋
書目名稱Cognitive Systems and Signal Processing讀者反饋學科排名
作者: 性滿足 時間: 2025-3-22 00:12 作者: Triglyceride 時間: 2025-3-22 02:22 作者: AMPLE 時間: 2025-3-22 06:58 作者: FEAT 時間: 2025-3-22 11:28
The Realtime Indoor Localization Unmanned Aerial Vehicleon of direct method and feature-based method. The visual odometer uses the photometric error to directly match and track the camera’s pose to improve the real-time performance. Then the ORB (Oriented FAST and Rotated Brief) features are extended from key frames, and local and global optimization can作者: 纖細 時間: 2025-3-22 12:59
L1-Norm and Trace Lasso Based Locality Correlation Projectionhe robustness to outliers too much and overlook the correlation information among data so that they usually encounter the instability problem. To overcome this problem, in this paper, we propose a method called L1-norm and trace Lasso based locality correlation projection (L1/TL-LRP), in which the r作者: 纖細 時間: 2025-3-22 17:46
Episodic Training for Domain Generalization Using Latent Domainsin. In this paper, take advantage of aggregating data method from all source and latent domains as a novel, we propose episodic training for domain generalization, aim to improve the performance during the trained model used for prediction in the unseen domain. To address this goal, we first designe作者: 舊石器時代 時間: 2025-3-22 23:01 作者: Confidential 時間: 2025-3-23 03:37
METAHACI: Meta-learning for Human Activity Classification from IMU Datameasurement unit (IMU) sensor is one of the popular devices collecting time-series data. Together with deep neural network implementation, this results in facilitating advancement in time series data analysis. However, the classical problem for the deep neural network is that it requires a vast amou作者: 監(jiān)禁 時間: 2025-3-23 05:43
Fusing Knowledge and Experience with?Graph Convolutional Network for?Cross-task Learning in Visual Cents prior methods to handle this task. Therefore, we propose a model called knowledge-experience fusion graph (KEFG) network for novel inference. It exploits information from both knowledge and experience. With the employment of graph convolutional network (GCN), KEFG generates the predictive class作者: pellagra 時間: 2025-3-23 11:00 作者: 易彎曲 時間: 2025-3-23 17:35
Path Planning and Simulation Based on Cumulative Error Estimation the environments. Most of the current methods consider the planning process alone instead of combining the planning results with tracking control, which leads to a significant reduction in the availability of the path, especially in complex scenarios with missing GPS and low positioning sensor accu作者: Lamina 時間: 2025-3-23 19:23
MIMF: Mutual Information-Driven Multimodal Fusionet recognition pattern. Due to the variant weather and road conditions, the real scenes can be far more complicated than those in the training dataset. That constructs a non-ignorable challenge for multimodal fusion models that obey fixed fusion modes, especially for autonomous driving. To address t作者: 陶醉 時間: 2025-3-24 00:32
Spatial Information Extraction of , Fields Using Multi-algorithm and Multi-sample Strategy-Based Remhe novel coronavirus patients. Accordingly, in this study, a variety of supervised intelligent algorithms based on multi-algorithm and multi-sample strategy (MAMS) are used to implement spatial distribution information extraction for distinctive landscape types under unique environmental conditions.作者: exostosis 時間: 2025-3-24 06:25
Application of Convolution BLS in AI Face-Changing Problemociety. On special occasions, there is an urgent need for a model that can autonomously determine whether an image has undergone AI face-exchanging processing.Proposed two convolutional structures based on the braod learning system (BLS), and give the specific algorithm flow. Using the convolution m作者: 分開如此和諧 時間: 2025-3-24 08:49
Cognitive Calculation Studied for Smart System to Lead Water Resources Managementsources management from an interdisciplinary perspective. The basic method steps are: first, the specific entry point of target management is defined as water resources information management; second, the water resources knowledge management is emphasized, and in particular, the eight kinds of knowl作者: 扔掉掐死你 時間: 2025-3-24 12:05 作者: apropos 時間: 2025-3-24 15:50
Zhixian Yan,Dipanjan Chakrabortycial intelligence. In vision fields, facial expression recognition aims to identify facial expressions through images or videos, but there is rare work towards real-world applications. In this work, we propose a hardware-friendly quantized separable residual network and developed a real-world facial作者: 外露 時間: 2025-3-24 21:54 作者: mydriatic 時間: 2025-3-25 01:49
Sense Inheritance in English Word-Formation, among EEG electrodes, we propose a multichannel EEG emotion recognition method using convolutional neural network (CNN) with functional connectivity as input. Specifically, the phase synchronization indices are employed to compute the EEG functional connectivity matrices. Then a CNN is proposed to 作者: 走調(diào) 時間: 2025-3-25 07:12 作者: 洞察力 時間: 2025-3-25 09:51
Type inference and type containment,on of direct method and feature-based method. The visual odometer uses the photometric error to directly match and track the camera’s pose to improve the real-time performance. Then the ORB (Oriented FAST and Rotated Brief) features are extended from key frames, and local and global optimization can作者: AVOID 時間: 2025-3-25 15:04 作者: 規(guī)章 時間: 2025-3-25 18:47
Semantics of Genitive Objects in Russianin. In this paper, take advantage of aggregating data method from all source and latent domains as a novel, we propose episodic training for domain generalization, aim to improve the performance during the trained model used for prediction in the unseen domain. To address this goal, we first designe作者: 數(shù)量 時間: 2025-3-25 20:52
Deep Structure as Logical Form,w precision and poor adaptability. In this paper, a novel attitude estimation algorithm based on the fusion model of extend Kalman filter (EKF) and long short-term memory (LSTM) is proposed, which is composed of two main process: the initial attitude estimation of EKF and the subsequent calibration 作者: 消散 時間: 2025-3-26 01:59 作者: debouch 時間: 2025-3-26 04:47
Semantics of Probabilistic Processesents prior methods to handle this task. Therefore, we propose a model called knowledge-experience fusion graph (KEFG) network for novel inference. It exploits information from both knowledge and experience. With the employment of graph convolutional network (GCN), KEFG generates the predictive class作者: BARK 時間: 2025-3-26 12:12
Testing Finitary Probabilistic Processes,lar value decomposition (SVD) of larger size matrix in big data and information processing. By factoring the matrix trace lasso into the squared sum of two Frobenius-norm, this work studies the solutions of both adaptive sparse representation (ASR) and correlation adaptive subspace segmentation (CAS作者: CANE 時間: 2025-3-26 16:21
Loose Real-Time Communicating Agents, the environments. Most of the current methods consider the planning process alone instead of combining the planning results with tracking control, which leads to a significant reduction in the availability of the path, especially in complex scenarios with missing GPS and low positioning sensor accu作者: 幼兒 時間: 2025-3-26 17:06 作者: Brittle 時間: 2025-3-26 22:28 作者: STIT 時間: 2025-3-27 02:44 作者: inflame 時間: 2025-3-27 05:49
https://doi.org/10.1007/978-3-030-94695-1sources management from an interdisciplinary perspective. The basic method steps are: first, the specific entry point of target management is defined as water resources information management; second, the water resources knowledge management is emphasized, and in particular, the eight kinds of knowl作者: 無所不知 時間: 2025-3-27 10:27
Communications in Computer and Information Sciencehttp://image.papertrans.cn/c/image/229135.jpg作者: 出生 時間: 2025-3-27 17:06
https://doi.org/10.1007/978-981-16-2336-3artificial intelligence; cognitive systems; computer networks; computer systems; computer vision; correla作者: 消音器 時間: 2025-3-27 18:40 作者: Cougar 時間: 2025-3-28 01:20
Conference proceedings 2021 2020, held in Zhuhai, China, in December 2020...The 59 revised papers presented were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections on algorithm; application; manipulation; bioinformatics; vision; and autonomous vehicles..作者: burnish 時間: 2025-3-28 02:55 作者: 灰心喪氣 時間: 2025-3-28 06:19
Fusing Knowledge and Experience with?Graph Convolutional Network for?Cross-task Learning in Visual Cifiers of the novel classes with few labeled samples. Experiments show that KEFG can decrease the training time by the fusion of the source information and also increase the classification accuracy in cross-task learning.作者: incubus 時間: 2025-3-28 11:30 作者: 蝕刻術 時間: 2025-3-28 17:59
Deep Structure as Logical Form,s algorithm is 50.515% lower on average than EKF under different working conditions when using mean squared error (MSE) as the evaluation indicator, which could be concluded that this novel algorithm performs better than EKF, and provides a new way for attitude estimation.作者: GUMP 時間: 2025-3-28 21:00
Testing Finitary Probabilistic Processes,ditions. Finally, numerical experiments to the subspace clustering can show the less timing consumptions than CASS and the nearby performance of our proposed method when compared with the existing segmentation methods like SSC, LRR, LSR and CASS.作者: Aromatic 時間: 2025-3-29 00:52
Semantics of Systems of Concurrent Processes KITTI and A2D2 datasets, in which we simulate the extreme malfunction of sensors like modality loss problem. The result demonstrates the benefit of our method in practical application, and informs the future research into development of multimodal fusion as well.作者: Induction 時間: 2025-3-29 05:26
https://doi.org/10.1007/978-3-030-94695-1of the second leap in human cognition, from a new perspective to explore how to apply the smart system studied ideas namely cognitive calculation studied for smart system to lead the innovative road of social development in the specific field of water resources management.作者: SPURN 時間: 2025-3-29 09:25 作者: 挑剔小責 時間: 2025-3-29 14:53 作者: Bravado 時間: 2025-3-29 19:17 作者: entrance 時間: 2025-3-29 19:59
MIMF: Mutual Information-Driven Multimodal Fusion KITTI and A2D2 datasets, in which we simulate the extreme malfunction of sensors like modality loss problem. The result demonstrates the benefit of our method in practical application, and informs the future research into development of multimodal fusion as well.作者: fleeting 時間: 2025-3-30 00:02
Cognitive Calculation Studied for Smart System to Lead Water Resources Managementof the second leap in human cognition, from a new perspective to explore how to apply the smart system studied ideas namely cognitive calculation studied for smart system to lead the innovative road of social development in the specific field of water resources management.作者: Inelasticity 時間: 2025-3-30 08:05
1865-0929 The papers are organized in topical sections on algorithm; application; manipulation; bioinformatics; vision; and autonomous vehicles..978-981-16-2335-6978-981-16-2336-3Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: FOLD 時間: 2025-3-30 11:57
Sense Inheritance in English Word-Formation,effectively extract the classification information of these functional connections. The experimental results based on the DEAP and SEED datasets validate the superior performance of the proposed method, compared with the input of raw EEG data. The code of the proposed model is available at ..作者: Diuretic 時間: 2025-3-30 14:49
Semantics of Probabilistic Processesifiers of the novel classes with few labeled samples. Experiments show that KEFG can decrease the training time by the fusion of the source information and also increase the classification accuracy in cross-task learning.作者: 噱頭 時間: 2025-3-30 16:57 作者: 樹膠 時間: 2025-3-30 21:59 作者: SEMI 時間: 2025-3-31 04:31 作者: 熱烈的歡迎 時間: 2025-3-31 05:35 作者: 背書 時間: 2025-3-31 12:51
Loose Real-Time Communicating Agents,g the dead-reckoning process and effectively reduces the cumulative error within the optimization process. The simulation conclusion in the 2D scene verifies the effectiveness of the algorithm for reducing the cumulative error.作者: nepotism 時間: 2025-3-31 15:06 作者: 搖擺 時間: 2025-3-31 17:32
Hole-Peg Assembly Strategy Based on Deep Reinforcement Learningate of deep reinforcement learning. The assembly task can be finished by the intelligent agent based on the measurement information of force-moment and the pose. In this paper, the training and verification of assembly verification is realized on the V-rep simulation platform and the UR5 manipulator.作者: incredulity 時間: 2025-3-31 22:18 作者: fidelity 時間: 2025-4-1 03:07
