標(biāo)題: Titlebook: Neural Information Processing; 28th International C Teddy Mantoro,Minho Lee,Achmad Nizar Hidayanto Conference proceedings 2021 Springer Nat [打印本頁] 作者: obesity 時(shí)間: 2025-3-21 17:24
書目名稱Neural Information Processing影響因子(影響力)
書目名稱Neural Information Processing影響因子(影響力)學(xué)科排名
書目名稱Neural Information Processing網(wǎng)絡(luò)公開度
書目名稱Neural Information Processing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Neural Information Processing被引頻次
書目名稱Neural Information Processing被引頻次學(xué)科排名
書目名稱Neural Information Processing年度引用
書目名稱Neural Information Processing年度引用學(xué)科排名
書目名稱Neural Information Processing讀者反饋
書目名稱Neural Information Processing讀者反饋學(xué)科排名
作者: EXUDE 時(shí)間: 2025-3-21 22:10 作者: 尊敬 時(shí)間: 2025-3-22 01:00 作者: 煞費(fèi)苦心 時(shí)間: 2025-3-22 07:33 作者: 考古學(xué) 時(shí)間: 2025-3-22 11:03
Metric Learning Based Vision Transformer for?Product Matching products. The proposed ML-VIT adopts Arcface loss to achieve intra-class compactness and inter-class dispersion. Compared with Siamese neural network and other pre-trained models in terms of F1 score and accuracy, ML-VIT is proved to yield modest embeddings for product image matching.作者: 獨(dú)輪車 時(shí)間: 2025-3-22 14:43 作者: 疼死我了 時(shí)間: 2025-3-22 20:29
A Focally Discriminative Loss for?Unsupervised Domain Adaptationiscrimination. The intergration of both losses makes the intra-class features close as well as push away the inter-class features far from each other. Moreover, the improved loss is simple yet effective. Our model shows state-of-the-art compared to the most domain adaptation methods.作者: blithe 時(shí)間: 2025-3-22 22:51
Learning Discriminative Representation with?Attention and?Diversity for?Large-Scale Face Recognitionenvalue decomposition or the approximation process. Visualization results illustrate that models with our attention module and diversity regularizers capture more critical localization information. And competitive performance on large-scale face recognition benchmark verifies the effectiveness of our approaches.作者: 開始發(fā)作 時(shí)間: 2025-3-23 05:12
Multi-task Perceptual Occlusion Face Detection with?Semantic Attention Networkon is selected and aggregated automatically to the task of occlusion face detection. Finally, MTOFD is tested and compared with some typical algorithms, such as FAN and AOFD, and it is found that our algorithm achieves state-of-the-art performance on dataset MAFA.作者: 處理 時(shí)間: 2025-3-23 05:55
RAIDU-Net: Image Inpainting via?Residual Attention Fusion and?Gated Information Distillationnd decoder, which can further extract useful low-level features from the generator. Experiments on public databases show that our RAIDU-Net architecture achieves promising results and outperforms the existing state-of-the-art methods.作者: PLAYS 時(shí)間: 2025-3-23 11:45 作者: encomiast 時(shí)間: 2025-3-23 17:23
erating system and application can be simultaneously run on the same host. In the VM environment the conventional hard disk drive (HDD) has limitations such as low random access performance and high power consumption. Solid State Drive (SSD) is an emerging storage technology, playing a critical role作者: 防水 時(shí)間: 2025-3-23 19:44 作者: 有幫助 時(shí)間: 2025-3-24 00:33 作者: 做方舟 時(shí)間: 2025-3-24 05:36
Zexuan Yin,Paolo Baruccaake repeated maintenance changes to software. This is particularly problematic when inaccurate estimates of the required resources leads to serious negotiation issues. The development of a Categorisation of Maintenance Effort (COME) matrix enables an overall summary of software maintenance changes a作者: 高爾夫 時(shí)間: 2025-3-24 08:36
Junjie Guo,Zhiyuan Ma,Haodong Zhao,Gongshen Liu,Xiaoyong Liect has a specific duration, consumes resources, and produces deliverables. From the perspective of a developer, a software project consists of project functions, activities and tasks. Figure?4.1 depicts a project model, as described by Bernd Bruegge (2004). A project function is an activity, or set作者: DEAF 時(shí)間: 2025-3-24 12:56
Neeraj Kumar,Ankur Narang,Brejesh lall,Srishti Goels and tools used in software engineering.A special chapter oThis textbook provides a progressive approach to the teaching of software engineering. First, readers are introduced to the core concepts of the object-oriented methodology, which is used throughout the book to act as the foundation for sof作者: 常到 時(shí)間: 2025-3-24 17:01
Dongting Sun,Mengzhu Wang,Xurui Ma,Tianming Zhang,Nan Yin,Wei Yu,Zhigang Luoect has a specific duration, consumes resources, and produces deliverables. From the perspective of a developer, a software project consists of project functions, activities and tasks. Figure?4.1 depicts a project model, as described by Bernd Bruegge (2004). A project function is an activity, or set作者: 高度表 時(shí)間: 2025-3-24 21:26 作者: pellagra 時(shí)間: 2025-3-25 00:15
Obed Tettey Nartey,Guowu Yang,Dorothy?Araba?Yakoba Agyapong,JinZhao Wu,Asare K. Sarpong,Lady Nadia F of software defect prediction in industrial settings is not eagerly shared by the pioneering companies. In particular, the cost effectiveness of using the DePress open source software measurement framework, developed by Wroclaw University of Science and Technology, and Capgemini software developmen作者: 拖債 時(shí)間: 2025-3-25 04:53
Linwei Zhang,Yeu-Shin Ful cooperation between industry and universities. In case of IT professionals, Ph.D. studies should be focused on strategic domains, advances in software engineering, and software system engineering. Moreover, development of IT architectures is crucial for software companies, and should become a vita作者: Melodrama 時(shí)間: 2025-3-25 11:13
Hanqi Wang,Xing Hu,Liang Song,Guanhua Zhang,Yang Liu,Jing Liu,Linhua Jiangl cooperation between industry and universities. In case of IT professionals, Ph.D. studies should be focused on strategic domains, advances in software engineering, and software system engineering. Moreover, development of IT architectures is crucial for software companies, and should become a vita作者: 啟發(fā) 時(shí)間: 2025-3-25 14:00
Zhong Zheng,Manli Zhang,Guixia Kang of software defect prediction in industrial settings is not eagerly shared by the pioneering companies. In particular, the cost effectiveness of using the DePress open source software measurement framework, developed by Wroclaw University of Science and Technology, and Capgemini software developmen作者: grenade 時(shí)間: 2025-3-25 16:49
Lian Shen,Jia-Xiang Lin,Chang-Ying Wangl cooperation between industry and universities. In case of IT professionals, Ph.D. studies should be focused on strategic domains, advances in software engineering, and software system engineering. Moreover, development of IT architectures is crucial for software companies, and should become a vita作者: 胖人手藝好 時(shí)間: 2025-3-25 23:04
Rakesh Kumar Sanodiya,Chinmay Sharma,Sai Satwik,Aravind Challa,Sathwik Rao,Leehter Yaold assume responsibility for its reliability. While "reliable" originally assumed implementations that were effective and mainly error-free, additional issues like adaptability and maintainability have gained equal importance recently. For example, the 2004 ACM/IEEE Software Engineering Curriculum G作者: 消耗 時(shí)間: 2025-3-26 00:22
Shunkai Zhou,Yueling Zhang,Guitao Cao,Jiangtao Wang comprising thousands of programs. More specifically, it studies the substitution of a modern data management technology for a legacy one. Platform migration raises two major issues. The first one is the conversion of the database to a new data management paradigm. Recent results have shown that aut作者: remission 時(shí)間: 2025-3-26 06:02 作者: 男生如果明白 時(shí)間: 2025-3-26 10:23 作者: 假 時(shí)間: 2025-3-26 12:46 作者: 異端邪說2 時(shí)間: 2025-3-26 17:18 作者: cornucopia 時(shí)間: 2025-3-26 21:00 作者: cogitate 時(shí)間: 2025-3-27 05:02 作者: Chagrin 時(shí)間: 2025-3-27 05:17 作者: 牢騷 時(shí)間: 2025-3-27 13:16
A Focally Discriminative Loss for?Unsupervised Domain Adaptationised domain adaptation (UDA), where both domains follow different distributions, and the labels from source domain are merely available. However, MMD and its class-wise variants possibly ignore the intra-class compactness, thus canceling out discriminability of feature representation. In this paper,作者: senile-dementia 時(shí)間: 2025-3-27 15:33
Automatic Drum Transcription with?Label Augmentation Using Convolutional Neural Networks The successful transcription of drum instruments is a key step in the analysis of drum music. Existing systems use the target drum instruments as a separate training objective, which faces the problems of over-fitting and limited performance improvement. To solve the above limitations, this paper p作者: RACE 時(shí)間: 2025-3-27 17:53
Adaptive Curriculum Learning for?Semi-supervised Segmentation of 3D CT-Scanses a challenge which prevents deep learning models from obtaining the results they have achieved most especially in the field of medical imaging. Recently, self-training with deep learning has become a powerful approach to leverage labelled training and unlabelled data. However, a challenge of gener作者: 性滿足 時(shí)間: 2025-3-27 23:00
Genetic Algorithm and?Distinctiveness Pruning in?the?Shallow Networks for?VehicleXf real data often brings up privacy and data security issues. This paper aims to build a shallow neural network model for the pre-trained synthetic feature dataset, VehicleX. Using genetic algorithm to reduce the dimensional complexity by randomly selecting a subset of features from before training.作者: 過份好問 時(shí)間: 2025-3-28 06:02
Stack Multiple Shallow Autoencoders into?a?Strong One: A?New Reconstruction-Based Method to?Detect A input from high-level features extracted from the samples. The underlying assumption of these methods is that a deep model trained on normal data would produce higher reconstruction error for abnormal input. But this underlying assumption is not always valid. Because the neural networks have a stro作者: GRIEF 時(shí)間: 2025-3-28 07:55 作者: Peculate 時(shí)間: 2025-3-28 12:31 作者: BRIDE 時(shí)間: 2025-3-28 17:45 作者: 匍匐前進(jìn) 時(shí)間: 2025-3-28 21:03
Sentence Rewriting with?Few-Shot Learning for?Document-Level Event Coreference Resolutioned event mention, due to their different expressions. Motivated by the recent successful application of the sentence rewriting models on information extraction and the fact that event triggers and arguments are beneficial for event coreference resolution, we employ the sentence rewriting mechanism t作者: Sciatica 時(shí)間: 2025-3-29 01:05 作者: 廢除 時(shí)間: 2025-3-29 04:39 作者: 付出 時(shí)間: 2025-3-29 10:04 作者: Osteoporosis 時(shí)間: 2025-3-29 12:54 作者: 繼承人 時(shí)間: 2025-3-29 16:31 作者: compassion 時(shí)間: 2025-3-29 20:29
978-3-030-92184-2Springer Nature Switzerland AG 2021作者: tackle 時(shí)間: 2025-3-30 00:24
Neural Information Processing978-3-030-92185-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Ptosis 時(shí)間: 2025-3-30 07:33
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/n/image/663584.jpg作者: 腐蝕 時(shí)間: 2025-3-30 11:31 作者: GULP 時(shí)間: 2025-3-30 15:20
Stochastic Recurrent Neural Network for?Multistep Time Series Forecastingows our model to be easily integrated into any deep architecture for sequential modelling. We test our model on a wide range of datasets from finance to healthcare; results show that the stochastic recurrent neural network consistently outperforms its deterministic counterpart.作者: 泥瓦匠 時(shí)間: 2025-3-30 19:02 作者: 邊緣 時(shí)間: 2025-3-30 21:05 作者: 親屬 時(shí)間: 2025-3-31 03:08 作者: Indicative 時(shí)間: 2025-3-31 06:52
Stack Multiple Shallow Autoencoders into?a?Strong One: A?New Reconstruction-Based Method to?Detect Af prior AE into the next one as input. For abnormal input, the iterative reconstruction process would gradually enlarge the reconstruction error. Our goal is to propose a general architecture that can be applied to different data types, e.g., video and image. For video data, we further introduce a w作者: ATRIA 時(shí)間: 2025-3-31 12:48 作者: Pandemic 時(shí)間: 2025-3-31 17:13
A Novel Metric Learning Framework for?Semi-supervised Domain Adaptationancy (MMD) criterion for feature matching and to construct new domain-invariant feature representations for both distribution differences and irrelevant instances. To validate the effectiveness of our approach we performed experiments on all tasks of the PIE face real-world dataset and compared the 作者: brassy 時(shí)間: 2025-3-31 21:25
Generating Adversarial Examples by?Distributed Upsamplingtifacts caused by deconvolution. We illustrate the performance of our method using experiments conducted on MNIST and CIFAR-10. The experiment results prove that adversarial examples generated by our method achieve a higher attack success rate and better transferability.作者: 莎草 時(shí)間: 2025-3-31 23:19 作者: Sarcoma 時(shí)間: 2025-4-1 04:47
