作者: 阻止 時(shí)間: 2025-3-21 21:38 作者: PAD416 時(shí)間: 2025-3-22 02:12 作者: Aviary 時(shí)間: 2025-3-22 08:08 作者: 星星 時(shí)間: 2025-3-22 11:55
https://doi.org/10.1007/1-4020-4350-3Controlling; Management; Manufacturing; Manufacturing System; Marketing; Statistical Process Control; plan作者: EWE 時(shí)間: 2025-3-22 14:25 作者: pulmonary-edema 時(shí)間: 2025-3-22 17:22 作者: HERE 時(shí)間: 2025-3-22 23:24
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: Scintillations 時(shí)間: 2025-3-23 03:01 作者: 脆弱帶來 時(shí)間: 2025-3-23 07:06 作者: Juvenile 時(shí)間: 2025-3-23 12:26
ataset shows that our best model detects laser-scar images with sensitivity of 0.962, specificity of 0.999, precision of 0.974 and AP of 0.988 and AUC of 0.999. The same model is tested on the public LMD-BAPT test set, obtaining sensitivity of 0.765, specificity of 1, precision of 1, AP of 0.975 and作者: GET 時(shí)間: 2025-3-23 17:41
ataset shows that our best model detects laser-scar images with sensitivity of 0.962, specificity of 0.999, precision of 0.974 and AP of 0.988 and AUC of 0.999. The same model is tested on the public LMD-BAPT test set, obtaining sensitivity of 0.765, specificity of 1, precision of 1, AP of 0.975 and作者: 不可比擬 時(shí)間: 2025-3-23 18:13 作者: 一致性 時(shí)間: 2025-3-24 00:33
el are unpaired sets of noisy and clean images. This paper explores the use of Generative Adversarial Networks (GAN) to generate denoised versions of the noisy documents. In particular, where paired information is available, we formulate the problem as an image-to-image translation task i.e, transla作者: 強(qiáng)所 時(shí)間: 2025-3-24 03:46
plate diagrams, unstructured shape of graphical objects to be identified and variability in the strokes of handwritten text. The proposed pipeline incorporates a capsule and spatial transformer network based classifier for accurate text reading, and a customized CTPN [.] network for text detection i作者: 血統(tǒng) 時(shí)間: 2025-3-24 06:32
plate diagrams, unstructured shape of graphical objects to be identified and variability in the strokes of handwritten text. The proposed pipeline incorporates a capsule and spatial transformer network based classifier for accurate text reading, and a customized CTPN [.] network for text detection i作者: DEMUR 時(shí)間: 2025-3-24 14:37 作者: 性冷淡 時(shí)間: 2025-3-24 17:14
radation kernel as the weighted combination of the basis kernels. With the learned degradation model, a large number of realistic HR-LR pairs can be easily generated to train a more robust SISR model. Extensive experiments are performed to quantitatively and qualitatively validate the proposed degra作者: FANG 時(shí)間: 2025-3-24 21:12 作者: 節(jié)省 時(shí)間: 2025-3-25 01:30
of a particular location in the 2D map. At test time, this embedding is extracted from a panoramic building instance label and depth images. It is then used to retrieve the closest match in the database..We evaluate our localization framework on two large-scale datasets consisting of Cambridge and 作者: 糾纏 時(shí)間: 2025-3-25 04:33 作者: 寵愛 時(shí)間: 2025-3-25 09:59 作者: 財(cái)主 時(shí)間: 2025-3-25 13:30
ed visible and thermal representations, and to minimize the distribution mismatch between the predictions of the visible and thermal images. Through adversarial learning, the proposed method leverages thermal images to construct better image representations and classifiers for visible images during 作者: FLORA 時(shí)間: 2025-3-25 15:50 作者: 容易生皺紋 時(shí)間: 2025-3-25 21:41
For example, in criminal investigations, gender classification may significantly minimize the list of potential subjects. Previous work mainly offered solutions for the task of gender classification based on complete fingerprints. However, partial fingerprint captures are frequently occurring in man作者: inhumane 時(shí)間: 2025-3-26 01:03 作者: collagenase 時(shí)間: 2025-3-26 06:46 作者: Constant 時(shí)間: 2025-3-26 10:30
behind circular or irregular scars in the retina. Laser scar detection in fundus images is thus important for automated DR screening. Despite its importance, the problem is understudied in terms of both datasets and methods. This paper makes the first attempt to detect laser-scar images by deep lear作者: chemical-peel 時(shí)間: 2025-3-26 16:22 作者: impale 時(shí)間: 2025-3-26 19:24 作者: 修飾 時(shí)間: 2025-3-26 21:45 作者: 顛簸下上 時(shí)間: 2025-3-27 03:12
ks the faulty machine regions on a paper outline of the machine. Over the years, millions of such inspection sheets have been recorded and the data within these sheets has remained inaccessible. However, with industries going digital and waking up?to the potential value of fault data for machine hea作者: 不自然 時(shí)間: 2025-3-27 05:18
ks the faulty machine regions on a paper outline of the machine. Over the years, millions of such inspection sheets have been recorded and the data within these sheets has remained inaccessible. However, with industries going digital and waking up?to the potential value of fault data for machine hea作者: inscribe 時(shí)間: 2025-3-27 11:25
ks the faulty machine regions on a paper outline of the machine. Over the years, millions of such inspection sheets have been recorded and the data within these sheets has remained inaccessible. However, with industries going digital and waking up?to the potential value of fault data for machine hea作者: BOOST 時(shí)間: 2025-3-27 14:13
ted by applying a simple degradation operator (e.g., bicubic downsampling) to its high-resolution (HR) counterpart, have limited generalization capability on real-world LR images, whose degradation process is much more complex. Several real-world SISR datasets have been constructed to reduce this ga作者: PRISE 時(shí)間: 2025-3-27 21:21
