標(biāo)題: Titlebook: Intelligence Science and Big Data Engineering. Visual Data Engineering; 9th International Co Zhen Cui,Jinshan Pan,Jian Yang Conference proc [打印本頁] 作者: Coarse 時(shí)間: 2025-3-21 20:02
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書目名稱Intelligence Science and Big Data Engineering. Visual Data Engineering影響因子(影響力)學(xué)科排名
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書目名稱Intelligence Science and Big Data Engineering. Visual Data Engineering網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Intelligence Science and Big Data Engineering. Visual Data Engineering被引頻次
書目名稱Intelligence Science and Big Data Engineering. Visual Data Engineering被引頻次學(xué)科排名
書目名稱Intelligence Science and Big Data Engineering. Visual Data Engineering年度引用
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書目名稱Intelligence Science and Big Data Engineering. Visual Data Engineering讀者反饋
書目名稱Intelligence Science and Big Data Engineering. Visual Data Engineering讀者反饋學(xué)科排名
作者: 惡心 時(shí)間: 2025-3-21 20:17
Intelligence Science and Big Data Engineering. Visual Data Engineering978-3-030-36189-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 異端邪說2 時(shí)間: 2025-3-22 01:19
https://doi.org/10.1007/978-3-030-36189-1artificial intelligence; computational linguistics; computer networks; computer vision; data mining; face作者: 神圣不可 時(shí)間: 2025-3-22 04:49 作者: 態(tài)度暖昧 時(shí)間: 2025-3-22 10:06 作者: Abnormal 時(shí)間: 2025-3-22 15:05
Adaptive Online Learning for Video Object Segmentation,arn how to online adapt the learned segmentation model to the specific testing video sequence and the corresponding future video frames, where the confidence patterns is employed to constrain/guide the implementation of adaptive learning process by fusing both object appearance and motion cue inform作者: 難聽的聲音 時(shí)間: 2025-3-22 19:15 作者: FIG 時(shí)間: 2025-3-22 23:53
Memory Network-Based Quality Normalization of Magnetic Resonance Images for Brain Segmentation, MemNet-based algorithm can not only normalize and improve the quality of brain MR images, but also enable the same 3D U-Net to produce substantially more accurate segmentation of major brain tissues.作者: 改正 時(shí)間: 2025-3-23 02:47
Sparse-Temporal Segment Network for Action Recognition,ontain the complementary features. Extensive experiments in subjective and objective show that temporal-sparse segment network can reach the accuracy of 94.2%, which is significantly better than several state-of-the-art algorithms.作者: BILK 時(shí)間: 2025-3-23 08:53 作者: 劇本 時(shí)間: 2025-3-23 13:10 作者: 同義聯(lián)想法 時(shí)間: 2025-3-23 16:00
Robust Object Tracking Based on Multi-granularity Sparse Representation,with different sizes. At last, in order to reduce tracking model’s drift phenomenon due to model update, an adaptive update mechanism is designed by combining occlusion ratio and incremental HOG feature. Both qualitative and quantitative evaluations have been conducted on OTB-2013 datasets to demons作者: spinal-stenosis 時(shí)間: 2025-3-23 18:11
Real-Time Visual Object Tracking Based on Reinforcement Learning with Twin Delayed Deep Deterministodel by using two Critic networks to jointly predict the bounding box confidence, and to obtain the smaller predicted value as the label to update the network parameters, thereby rendering the Critic network to avoid excessive estimation bias, accelerate the convergence of the loss function, and obt作者: 潛移默化 時(shí)間: 2025-3-23 23:07
Efficiently Handling Scale Variation for Pedestrian Detection, and only introduces very few additional parameters. We have conducted experiments on the CityPersons, Caltech and ETH datasets and achieved significant improvements to the baseline method, especially on the small scale subset. In particular, on the CityPersons and ETH datasets, our method surpasses作者: Foolproof 時(shí)間: 2025-3-24 05:34 作者: CAMP 時(shí)間: 2025-3-24 06:30 作者: 莎草 時(shí)間: 2025-3-24 11:48
Soft Transferring and Progressive Learning for Human Action Recognition,to learn from the supervisors, which have been trained on large-scale datasets. We fine-tune supervision model and train our new model on UCF101 and HMDB51 datasets, experiment results demonstrate the feasibility of soft transferring method, extend transfer learning to a broader sense, and show the 作者: MOAN 時(shí)間: 2025-3-24 16:17 作者: 斷斷續(xù)續(xù) 時(shí)間: 2025-3-24 22:45 作者: 熔巖 時(shí)間: 2025-3-24 23:25 作者: Melatonin 時(shí)間: 2025-3-25 06:21
Zhipu Liu,Lei Zhangrates durch die Menschen selber. Zeigt sich doch heute schon, da? die universale Idee des Reiches gegenwartsgem??er ist als der nominalistische Staatsgedanke. Denn w?hrend letzterer zum Chaos ?souver?ner“ Nationalstaaten führte, liegt im Ordo des Reichs das Vorbildliche auch für neue Wege, die Einhe作者: GLADE 時(shí)間: 2025-3-25 08:18 作者: 費(fèi)解 時(shí)間: 2025-3-25 14:55
Mikro?konomie bewegen, solange wir nicht auf die fundamentalen Konzepte der Wirtschaftstheorie, wie wir sie in den Schriften der marginalistischen Schule (ca. 1870 – 1910) oder in den Schriften von Karl Marx oder von Ricardo oder Adam Smith vorfinden. Ja, es gibt sogar welche (und ihre Zahl nimmt la作者: 浪費(fèi)物質(zhì) 時(shí)間: 2025-3-25 17:27
Yang Liu,Jinshan Pan,Zhixun Su Woher diese Individuen kommen, wie sie unterstützt werden, worauf sie ihre Pr?ferenzen gründen, wie und durch wen die Waren produziert werden und durch welche Macht die ?Anfangsausstattungen“ zugeteilt werden — all das wird als unerheblich für die Begründung des Tauschwertes angesehen. Wie auch imm作者: hankering 時(shí)間: 2025-3-25 20:00 作者: 令人不快 時(shí)間: 2025-3-26 01:33
Kaixuan Chen,Gengxin Xu,Jiaying Qian,Chuan-Xian Renrer Bewu?theit, unserer Phantasie und unseres Spieltriebs. Sie ist verdinglichter Planungsakt ebenso wie Modell und Vorstellung von der Welt. Die Technisierung veranla?t zum denkerischen Probehandeln, symbolisiert T?tigkeiten, das eigene überflüssigsein und ist ein Medium unseres p?dagogischen und p作者: electrolyte 時(shí)間: 2025-3-26 06:23 作者: 分散 時(shí)間: 2025-3-26 11:19
Jing Du,Yang Xu,Zhihui Weisowie die diesbezüglichen Ausführungen zur Redepflicht (bzw. gro?e Redepflicht nach § 321 II HGB) einen breiten Raum ein. Die Ausführungen orientieren sich dabei haupts?chlich an den Informationsinteressen und -bedürfnissen des Aufsichtsrates als erstem und wichtigstem Adressaten. Die Arbeit tr?gt j作者: crockery 時(shí)間: 2025-3-26 16:18 作者: 虛弱 時(shí)間: 2025-3-26 17:39
Songze Tang,Mingyue Qiu beraten Andere, ob wir darum gebeten werden oder nicht, ob wir von dem fraglichen Sachverhalt etwas verstehen oder nicht und ob wir von einem Befolgen unseres Rates profitieren oder nicht. Solche ?Alltagsberatung ‘kann als ein ubiquit?res kommunikatives Ereignis angesehen werden.作者: 暗諷 時(shí)間: 2025-3-26 21:37
Smoother Soft-NMS for Overlapping Object Detection in X-Ray Images,作者: CHASM 時(shí)間: 2025-3-27 05:05 作者: CHART 時(shí)間: 2025-3-27 05:50 作者: 清唱?jiǎng)?nbsp; 時(shí)間: 2025-3-27 12:09 作者: 名義上 時(shí)間: 2025-3-27 17:20
Egomotion Estimation Under Planar Motion with an RGB-D Camera,ometry framework. We evaluate our algorithm on the synthetic data and show the application on the real-world data. The experiments show that the proposed approach is efficient and robust enough for egomotion estimation in the Manhattan-like environments compared with the state-of-the-art methods.作者: Traumatic-Grief 時(shí)間: 2025-3-27 19:26
A Bypass-Based U-Net for Medical Image Segmentation,twork based on U-Net as well. The experimental results show that the proposed bypass-based U-Net can gain further context information, especially the details from the previous convolutional layer, and outperforms the original U-Net on the DRIVE dataset for retinal vessel segmentation and the ISBI 2018 challenge for skin lesion segmentation.作者: 痛打 時(shí)間: 2025-3-27 23:25 作者: 驕傲 時(shí)間: 2025-3-28 04:01
Conference proceedings 2019theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning...?.作者: Hemiplegia 時(shí)間: 2025-3-28 09:44 作者: 任意 時(shí)間: 2025-3-28 10:53 作者: 哀求 時(shí)間: 2025-3-28 18:33 作者: 施舍 時(shí)間: 2025-3-28 19:14
Adaptive Online Learning for Video Object Segmentation,y an annotated first frame. Previous VOS methods based on deep neural networks often solves this problem by fine-tuning the segmentation model in the first frame of the test video sequence, which is time-consuming and can not be well adapted to the current target video. In this paper, we proposed th作者: 懶洋洋 時(shí)間: 2025-3-29 01:09
Proposal-Aware Visual Saliency Detection with Semantic Attention,ention mechanism, semantic attention (SeA). The attention are established based on the observation that regions with high attention should have similarly semantic concepts with salient objects. The SeA takes the high-level semantic features from Faster Region-based Convolutional Neural Network (Fast作者: 使害怕 時(shí)間: 2025-3-29 06:15
Constrainted Subspace Low-Rank Representation with Spatial-Spectral Total Variation for Hyperspectre separated into different classification based on the land-covers, which means the spectral space can be regarded as an union of several low-rank subspaces. Subspace low-rank representation (SLRR) is a powerful tool in exploring the inner low-rank structure of spectral space and has been applied fo作者: 侵蝕 時(shí)間: 2025-3-29 09:55 作者: leniency 時(shí)間: 2025-3-29 14:50
Egomotion Estimation Under Planar Motion with an RGB-D Camera,als with the corridor-like structured scenarios and uses the prior knowledge of the environment: when at least one vertical plane is detected using the depth data, egomotion is estimated with one normal of the vertical plane and one point; when there are no vertical planes, a 2-point homography-base作者: Cirrhosis 時(shí)間: 2025-3-29 18:19
Sparse-Temporal Segment Network for Action Recognition,work, the sparse-temporal segment network to recognize human actions is proposed. Considering the sparse features contains the information of moving objects in videos, for example marginal information which is helpful to capture the target region and reduce the interference from similar actions, the作者: floaters 時(shí)間: 2025-3-29 22:40 作者: murmur 時(shí)間: 2025-3-30 03:23
Deep Blind Image Inpainting,ume that the positions of the corrupted regions are known. Different from existing methods that usually make some assumptions on the corrupted regions, we present an efficient blind image inpainting algorithm to directly restore a clear image from a corrupted input. Our algorithm is motivated by the作者: 拋射物 時(shí)間: 2025-3-30 07:21 作者: Fibrin 時(shí)間: 2025-3-30 09:09
A Bypass-Based U-Net for Medical Image Segmentation, how fully convolutional network (FCN) makes dense predictions, we modify U-Net by adding a new bypass for the expansive path. Before combining the contracting path with the upsampled output, we connect with the feature maps from a deeper encoding convolutional layer for the decoding up-convolutiona作者: Adulterate 時(shí)間: 2025-3-30 15:25
Real-Time Visual Object Tracking Based on Reinforcement Learning with Twin Delayed Deep Determinists, fast object motion and occlusion et al. affect a lot the robustness or accuracy of existing object tracking methods. This paper proposes a reinforcement learning model based on Twin Delayed Deep Deterministic algorithm (TD3) for single object tracking. The model is based on the deep reinforcement作者: intercede 時(shí)間: 2025-3-30 18:19 作者: Sputum 時(shí)間: 2025-3-30 23:31 作者: output 時(shí)間: 2025-3-31 03:43 作者: Migratory 時(shí)間: 2025-3-31 06:12
Soft Transferring and Progressive Learning for Human Action Recognition,tream datasets. Inevitably, one question occurs to us: is there any transferable characterizes between different models? In this paper, we discuss such problem by introducing a cross-architecture transferring learning scheme, dubbed soft transferring learning, aiming to overcome the limitation of di作者: infinite 時(shí)間: 2025-3-31 10:28 作者: BOLT 時(shí)間: 2025-3-31 15:38 作者: 使聲音降低 時(shí)間: 2025-3-31 17:35
sondern als eines geistigen Ph?nomens und in seinem inneren Verh?ltnis zur menschlichen Seele, wird bald einsehen, da? der Gedanke dieses Staates für sich allein nicht begriffen werden kann. Denn der moderne Staat besitzt kein geistiges Eigenlicht, sondern er tr?gt einen wie mondhaften Charakter, de作者: Fibrillation 時(shí)間: 2025-4-1 01:00
hen au?erordentlich gro?e Meinungsunterschiede. Die etablierteren und bedeutenderen Führer der sogenannten ?neoklassischen“ Schule — der nunmehr seit einem halben Jahrhundert herrschenden Schule — würden behaupten, da? die Krise nichts mehr ist als eine Art von Verwirrung, in die jede wissenschaftli作者: cloture 時(shí)間: 2025-4-1 04:34
Yang Liu,Jinshan Pan,Zhixun Su. Die Theorie weist nach, da? unter den vorausgesetzten Bedingungen alle Beteiligten aus dem Tausch einen Gewinn — ausgedrückt in ihren subjektiven Pr?ferenzen — ziehen. Diese überlegung findet sich in verallgemeinerter Form in der Theorie der optimalen Allokation von knappen Mitteln durch den Preis作者: Offbeat 時(shí)間: 2025-4-1 07:12 作者: LANCE 時(shí)間: 2025-4-1 14:10
Kaixuan Chen,Gengxin Xu,Jiaying Qian,Chuan-Xian Ren-politischen Systems, sondern gleichzeitig die Ver?nderung unserer allt?glichen Lebenswelt, unserer Gewohnheiten und Gew?hnlichkeiten. Und hierin Hegt sozusagen das Dramatische, die erlebte, fragwürdige Schicksalhaftigkeit. Die Lebenswelt ist der Horizont unseres kulturellen Wissensvorrates und unse
