作者: 共同確定為確 時間: 2025-3-21 20:21 作者: oncologist 時間: 2025-3-22 03:24 作者: 翻動 時間: 2025-3-22 08:23 作者: 同義聯(lián)想法 時間: 2025-3-22 12:32 作者: 安心地散步 時間: 2025-3-22 16:56
Hidden Aztecs and Absent Spaniards (CrossNet). We have creatively introduced the . structure, where the feature map of depthwise convolutions can be reused within the same . by cross connection. Such a design can make the CrossNet have high performance while less computing resource, especially suitable for mobile devices with very l作者: 安心地散步 時間: 2025-3-22 20:22 作者: 大喘氣 時間: 2025-3-22 21:56 作者: Culpable 時間: 2025-3-23 01:51
Higher Education Research in Europetructured data like 3D point clouds containing irregular neighborhoods constantly breaks the grid-based data assumption. Therefore applying best-practices and design choices from 2D-image learning methods towards processing point clouds are not readily possible. In this work, we introduce a natural 作者: Oligarchy 時間: 2025-3-23 06:00 作者: certitude 時間: 2025-3-23 11:48
https://doi.org/10.1007/978-0-306-48368-4ficulties in obtaining training data and the absence of color images. Thus, overall performance heavily depends on individual human skill in tuning hundreds of parameters. This paper presents a defect inspection technique using a defect probability image (DPI) and a deep convolutional neural network作者: Vaginismus 時間: 2025-3-23 15:28
Fusing Solar and Stellar Cosmologies,roducing the ability to reason about objects at the level of their constituent parts. While classic retrieval systems can only formulate simple searches such as . our new approach can formulate advanced and semantically meaningful search queries such as: .. Many applications could benefit from such 作者: MIR 時間: 2025-3-23 21:16 作者: Commission 時間: 2025-3-23 22:17
Contrasting Competitive Plausibility,s using deep convolutional neural networks (CNN). Face detection is implemented with region-based framework as previous work like Faster RCNN. We model the pose estimation as a classification and regression problem: first divide continuous head poses into several discrete clusters, then adjust poses作者: hemophilia 時間: 2025-3-24 04:26 作者: Medicaid 時間: 2025-3-24 07:21 作者: GUMP 時間: 2025-3-24 13:06 作者: 故意釣到白楊 時間: 2025-3-24 18:10
What Made the Renaissance in Europe?,om unlabeled data. In this paper, we propose an unsupervised deep learning framework to provide a potential solution for the problem that existing deep learning techniques require large labeled data sets for completing the training process. Our proposed introduces a new principle of joint learning o作者: 平項山 時間: 2025-3-24 19:22
The Alhazen Optical Revolution,the affine parameters consistent with a pre-estimated epipolar geometry from the point coordinates and the scales and rotations which the feature detector obtains. The closed-form solution is given as the roots of a quadratic polynomial equation, thus having two possible real candidates and fast pro作者: Hla461 時間: 2025-3-25 01:31 作者: Abjure 時間: 2025-3-25 05:17 作者: LINES 時間: 2025-3-25 08:34 作者: 保留 時間: 2025-3-25 13:11 作者: 幼稚 時間: 2025-3-25 17:16 作者: Urea508 時間: 2025-3-25 23:34
Flex-Convolutionall benchmark sets using fewer parameters and lower memory consumption and obtain significant improvements on a million-scale real-world dataset. Ours is the first which allows to efficiently process 7 million points ..作者: Melatonin 時間: 2025-3-26 01:39 作者: 偏見 時間: 2025-3-26 08:18 作者: Fsh238 時間: 2025-3-26 09:56 作者: 外形 時間: 2025-3-26 13:28 作者: 作繭自縛 時間: 2025-3-26 17:49 作者: 變化 時間: 2025-3-26 23:57 作者: GEM 時間: 2025-3-27 05:03
Hidden Aztecs and Absent Spaniards state-of-the-art performance of lightweight networks (such as MobileNets-V1/-V2, ShuffleNets and CondenseNet). We have tested the actual inference time on an ARM-based mobile device. The CrossNet still gets the best performance. Code and models are public available (.).作者: Tempor 時間: 2025-3-27 08:26 作者: 太空 時間: 2025-3-27 12:27
Contrasting Competitive Plausibility, as far as we know. Moreover, it is able to predict pose without using any 3D information. Extensive evaluations on several challenging benchmarks such as AFLW and AFW demonstrate the effectiveness of the proposed method with competitive results.作者: Cupidity 時間: 2025-3-27 16:19
The Alhazen Optical Revolution, leads to accurate ACs. Also, the estimated homographies have similar accuracy to what the state-of-the-art methods obtain, but due to requiring only a single correspondence, the robust estimation, e.g. by Graph-Cut RANSAC, is an order of magnitude faster.作者: CAGE 時間: 2025-3-27 21:08
Pioneer Networks: Progressively Growing Generative Autoencodere network with the recently introduced adversarial encoder–generator network. The ability to reconstruct input images is crucial in many real-world applications, and allows for precise intelligent manipulation of existing images. We show promising results in image synthesis and inference, with state-of-the-art results in . inference tasks.作者: Decline 時間: 2025-3-27 22:46 作者: 向外供接觸 時間: 2025-3-28 02:45 作者: 補充 時間: 2025-3-28 09:50 作者: trigger 時間: 2025-3-28 11:59 作者: 推測 時間: 2025-3-28 17:43 作者: allergen 時間: 2025-3-28 22:43 作者: Evocative 時間: 2025-3-28 23:43
3D Pick & Mix: Object Part Blending in Joint Shape and Image Manifoldses such as . our new approach can formulate advanced and semantically meaningful search queries such as: .. Many applications could benefit from such rich queries, users could browse through catalogues of furniture and . and . parts, combining for example the legs of a chair from one shop and the armrests from another shop.作者: CLAIM 時間: 2025-3-29 03:24
Dual Generator Generative Adversarial Networks for Multi-domain Image-to-Image Translationsistency and better stability. Extensive experiments on six publicly available datasets with different scenarios, ., architectural buildings, seasons, landscape and human faces, demonstrate that the proposed G.GAN achieves superior model capacity and better generation performance comparing with exis作者: Aprope 時間: 2025-3-29 09:08
Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneouslye can address both the generation and editing problem by training the proposed GANs, namely Editable GAN. For qualitative and quantitative evaluations, the proposed GANs outperform recent algorithms addressing the same problem. Also, we show that our model can achieve the competitive performance wit作者: Capture 時間: 2025-3-29 12:10
Answer Distillation for Visual Question Answeringion architecture. The results show that our method can effectively compress the answer space and improve the accuracy on open-ended task, providing a new state-of-the-art performance on COCO-VQA dataset.作者: 發(fā)酵劑 時間: 2025-3-29 18:06
Spiral-Net with F1-Based Optimization for Image-Based Crack Detectionn effective optimization method to train the network. The proposed network is extended from U-Net to extract more detailed visual features, and the optimization method is formulated based on F1 score (F-measure) for properly learning the network even on the highly imbalanced training samples. The ex作者: 獨行者 時間: 2025-3-29 21:31
Minutiae-Based Gender Estimation for Full and Partial Fingerprints of Arbitrary Size and Shape obtain an enhanced gender decision. Unlike classical solutions this allows to deal with unconstrained fingerprint parts of arbitrary size and shape. We performed investigations on a publicly available database and our proposed solution proved to significantly outperform state-of-the-art approaches 作者: aphasia 時間: 2025-3-30 03:37
Progressive Feature Fusion Network for Realistic Image Dehazingpared with popular state-of-the-art methods. With efficient GPU memory usage, it can satisfactorily recover ultra high definition hazed image up?to 4K resolution, which is unaffordable by many deep learning based dehazing algorithms.作者: Connotation 時間: 2025-3-30 07:55 作者: 卵石 時間: 2025-3-30 10:17
An Unsupervised Deep Learning Framework via Integrated Optimization of Representation Learning and Gles the GMM to achieve the best possible modeling of the data representations and each Gaussian component corresponds to a compact cluster, maximizing the second term will enhance the separability of the Gaussian components and hence the inter-cluster distances. As a result, the compactness of clust作者: 閹割 時間: 2025-3-30 15:07 作者: languid 時間: 2025-3-30 17:07 作者: musicologist 時間: 2025-3-30 21:31
Aspiring Tyrants and Theatrical Defianceion architecture. The results show that our method can effectively compress the answer space and improve the accuracy on open-ended task, providing a new state-of-the-art performance on COCO-VQA dataset.作者: 蘑菇 時間: 2025-3-31 04:07
https://doi.org/10.1007/978-0-306-48368-4n effective optimization method to train the network. The proposed network is extended from U-Net to extract more detailed visual features, and the optimization method is formulated based on F1 score (F-measure) for properly learning the network even on the highly imbalanced training samples. The ex作者: bronchodilator 時間: 2025-3-31 07:56 作者: Cerumen 時間: 2025-3-31 09:55 作者: laceration 時間: 2025-3-31 14:56
https://doi.org/10.1057/9780230601215ference set of photo-sketch pairs together with a large face photo dataset without ground truth sketches. Experiments show that our method achieves state-of-the-art performance both on public benchmarks and face photos in the wild. Codes are available at ..作者: AV-node 時間: 2025-3-31 20:48 作者: 消息靈通 時間: 2025-3-31 21:40
Dual Generator Generative Adversarial Networks for Multi-domain Image-to-Image Translationain using unpaired image data. However, these methods require the training of one specific model for every pair of image domains, which limits the scalability in dealing with more than two image domains. In addition, the training stage of these methods has the common problem of model collapse that d作者: 赦免 時間: 2025-4-1 03:03
