Alexis de Tocqueville; chronicler of the American democratic experiment

[Abstract]: The purpose of this work is to develop an interactive tool which helps botanists to extract the vein system with its hierarchical properties with as little user interaction as possible. In this paper, we present a new venation extraction method using independent component analysis (ICA). The popular and efficient FastICA algorithm is applied to patches of leaf images to learn a set of linear basis functions or features for the images and then the basis functions are used as the pattern map for vein extraction. In our experiments, the training sets are randomly generated from different leaf images. Experimental results demonstrate that ICA is a promising technique for extracting leaf veins and edges of objects. ICA, therefore, can play an important role in automatically identifying living plants

Depth Assisted Full Resolution Network for Single Image-based View Synthesis

Researches in novel viewpoint synthesis majorly focus on interpolation from multi-view input images. In this paper, we focus on a more challenging and ill-posed problem that is to synthesize novel viewpoints from one single input image. To achieve this goal, we propose a novel deep learning-based technique. We design a full resolution network that extracts local image features with the same resolution of the input, which contributes to derive high resolution and prevent blurry artifacts in the final synthesized images. We also involve a pre-trained depth estimation network into our system, and thus 3D information is able to be utilized to infer the flow field between the input and the target image. Since the depth network is trained by depth order information between arbitrary pairs of points in the scene, global image features are also involved into our system. Finally, a synthesis layer is used to not only warp the observed pixels to the desired positions but also hallucinate the missing pixels with recorded pixels. Experiments show that our technique performs well on images of various scenes, and outperforms the state-of-the-art techniques

Microwave-mediated heat transport through a quantum dot

The thermoelectric effect in a quantum dot (QD) attached to two leads in the presence of microwave fields is studied by using the Keldysh nonequilibrium Green function technique. When the microwave is applied only on the QD and in the linear-response regime, the main peaks in the thermoelectric figure of merit and the thermopower are found to decrease, with the emergence of a set of photon-induced peaks. Under this condition the microwave field can not generate heat current or electrical bias voltage. Surprisingly, when the microwave field is applied only to one (bright) lead and not to the other (dark) lead or the QD, heat flows mostly from the dark to the bright lead, almost irrespectively to the direction of the thermal gradient. We attribute this effect to microwave-induced opening of additional transport channels below the Fermi energy. The microwave field can change both the magnitude and the sign of the electrical bias voltage induced by the temperature gradient.Comment: 5 figur