91 research outputs found
Recovery of Methane Intercalated in Natural Gas Hydrate Sediments Using a Carbon Dioxide and Flue Gas Mixture
No full textConvergent paired electrolysis for zinc-mediated diastereoselective cinnamylation of α-amino esters
No full textA paired electrochemical method is presented for the one-pot synthesis of ?,d-unsaturated a-amino esters. The method involves the in situ generation of organozinc reagents through zinc chloride reduction on the nickel cathode and the TEMPO-mediated oxidation of amino esters on the carbon anode. The presence of an ester moiety in the amine substrate was found to be crucial for achieving high diastereoselectivity.
Intercalated methane production in natural gas hydrate sediments using a carbon dioxide and flue gas mixture
No full textPrimate ventral striatum maintains neural representations of the value of previously rewarded objects for habitual seeking
No full textThe ventral striatum (VS) is considered a key region that flexibly updates recent changes in reward values for habit learning. However, this update process may not serve to maintain learned habitual behaviors, which are insensitive to value changes. Here, using fMRI in humans and single-unit electrophysiology in macaque monkeys we report another role of the primate VS: that the value memory subserving habitual seeking is stably maintained in the VS. Days after object-value associative learning, human and monkey VS continue to show increased responses to previously rewarded objects, even when no immediate reward outcomes are expected. The similarity of neural response patterns to each rewarded object increases after learning among participants who display habitual seeking. Our data show that long-term memory of high-valued objects is retained as a single representation in the VS and may be utilized to evaluate visual stimuli automatically to guide habitual behavior. Ventral striatum is known to be involved in the value update for habit learning. Here, the authors report neural and behavioural correlates for the long-term maintenance of value memory for previously rewarded objects in the ventral striatum of humans and monkeys.Y
듀얼 픽셀 센서를 적용한 단일 카메라에서의 얼굴 복원 연구
No full text학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2021.2,[iv, 40 p. :]Dual pixel (DP) sensors built with two photodiodes under a tiny microlens provide a narrow baseline stereo images. Recently, many mobile manufacturers have adopted DP in their flagship models because it supports the faster auto-focus and more aesthetic image captures. Despite of the advantages of DP, research on their use for facial recognition has been limited, due to the lack of a public dataset. In this paper, we present the first DP facial geometry dataset involving more than 100K face images, the corresponding full 3D models in metric scale, and normal maps for 107 subjects. To acquire the datasets, we design a new multi-camera array consisting of 8~DSLR cameras with DP sensors, and propose a Structured Light (SL)-based facial 3D reconstruction method. Moreover, we propose a new stereo matching network for dual pixel images, called SubMat. We design a subpixel-level matching module tailored for stereo matching of extremely narrow baseline images. Extensive experiments show SubMat enables to produce the accurate depth maps and the estimates help to detect face spoofing. We demonstrate that the proposed method trained on our facial datasets achieves state-of-the-art performance on DP stereo matching.한국과학기술원 :전기및전자공학부
Deep Learning for Toxicity and Disease Prediction
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
Inherent Receptive Fields in the Early Layer Enable Continual Learning Under Dynamic Environments
No full text
CMSNet: Deep Color and Monochrome Stereo
No full textIn this paper, we propose an end-to-end convolutional neural network for stereo matching with color and monochrome cameras, called CMSNet (Color and Monochrome Stereo Network). Both cameras have the same structure except for the presence of a Bayer filter, but have a fundamental trade-off. The Bayer filter allows capturing chrominance information of scenes, but limits a quantum efficiency of cameras, which causes severe image noise. It seems ideal if we can take advantage of both the cameras so that we obtain noise-free images with their corresponding disparity maps. However, image luminance recorded from a color camera is not consistent with that from a monochrome camera due to spatially-varying illumination and different spectral sensitivities of the cameras. This degrades the performance of stereo matching. To solve this problem, we design CMSNet for disparity estimation from noisy color and relatively clean monochrome images. CMSNet also infers a noise-free image with the estimated disparity map. We leverage a data augmentation to simulate realistic signal-dependent noise and various radiometric distortions between input stereo pairs to train CMSNet effectively. CMSNet is evaluated using various datasets and the performance of our disparity estimation and image enhancement consistently outperforms state-of-the-art methods. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.FALSEsciescopu
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