Titlebook: Information and Communication Technologies; International Confer Vinu V Das,R. Vijaykumar Conference proceedings 2010 Springer-Verlag Berli

Picks-Disease

Rajat Sheel Jain,Neeraj Kumar,Brijesh Kumar as lighting, occlusion or self-occlusion in scenes happens. We argue that there could be multiple 3D human meshes corresponding a single image from a view point, because we really do not know what happens in extreme lighting or behind occlusion/self occlusion. In this paper, we address the problem

NICE

Manash Pratim Sarma,Kandarpa Kumar Sarma graphs to extract discriminative features. However, due to the fixed topology shared among different poses and the lack of direct long-range temporal dependencies, it is not trivial to learn the robust spatial-temporal feature. Therefore, we present a spatial-temporal adaptive graph convolutional n

Lice692

K. Dhanumjaya,G. Kiran Kumar,M. N. Giriprasad,M. Raja Reddymodels have a limited generalization ability under the scale and location mismatch between objects, as only few samples from target classes are provided. Therefore, the lack of a mechanism to match the scale and location between pairs of compared images leads to the performance degradation. The impo

知識分子

Prasenjit Choudhury,Rajasekhar Gaddam,Rajesh Babu Parisi,Manohar Babu Dasari,Satyanarayana Vuppalamodels have a limited generalization ability under the scale and location mismatch between objects, as only few samples from target classes are provided. Therefore, the lack of a mechanism to match the scale and location between pairs of compared images leads to the performance degradation. The impo

不公開

Nerve-Block

生命層

Silpakesav Velagaleti,Pavankumar Gorpuni,K. K. Mahapatraity of existing networks are relatively fixed, which makes it difficult for them to be flexibly applied to devices with different computational constraints. Instead of manually designing the network structure for each specific device, in this paper, we propose a novel training-free neural architectu

ENNUI

Ankita Tijare,Pravin Dakholest generative ZSL methods exploit category semantic plus Gaussian noise to generate visual features. However, there is a contradiction between the unity of category semantic and the diversity of visual features. The semantic of a single category cannot accurately correspond to different individuals

MIRTH

Genome