Sumantra Dutta Roy, Poonam Suryanarayan, "The Relation between discrete convolution /correlation and string matching, and exploring the possibility of a deterministic linear-time algorithm for discrete convolution/correlation" in Proc. IETE Journal of education, vol.51,April 2010....
The SCLSM method has shown promise in improving VQA model robustness by reducing the reliance on linguistic biases, thus encouraging the model to focus on the multimodal correlation between questions and images. While contrastive learning demonstrates significant potential for noise reduction in dependency...
A 'Relation Graph' is a graphical structure where objects are represented as nodes and the relationships among objects are represented as edges. It is commonly used in computer science to model spatial relations and interactions between entities. ...
To facilitate fair evaluation, we adopt the same backbones as the previous work (Liang, Lin, Fu, Zhu, and Li, 2022), where a simple CNN consisting of two convolution layers and two fully-connected layers is used for CIFAR-10 and CIFAR-100, and ResNet-18 (He, Zhang, Ren, and Sun,...
Relation Between Mean Median and Mode Relation between Laplace Transform and Fourier Transform Relation among Illumination, Brightness, and Luminous Intensity Relation between deep learning and machine learning Signals and Systems – Relation between Convolution and Correlation Components of IoT and Relation ...
The error bars of DN and D* derive from the uncertainty of next-higher-harmonic fit. The error bars of Darc mainly derive from those of yarc. (c) Same as b, but scaled by Tc. (d) Correlation between Tc and DN for Bi2212 from the present study (coloured circles). Also plotted ...
Moreover, the POS tags con- vey the syntactic information that could help to improve the preci- sion of relation extraction, as it is observed that there is strong correlation between ''VBD" (POS tag) and ''B-f2p" (R-MIMO tag) in dataset. The CAP tags are added as input to ...
where Xi is the original distributed representation of the node, Xi^ fuses local features in the graph, m is the number of nodes, d1 is the dimension of original representation, and GCN is graph convolution calculation. A vanilla GCN layer [39] (as shown in formula 3) is utilized to im...
Convolutional Layer: The input structure is subjected to convolution procedures employing several kernels Zelenko et al. (2003), Culotta and Sorensen (2004) or layers in the convolutional layer. The input is passed through such filters which locate particular patterns or attributes. The filters assist...
On this ground, we summarize in our work interpersonal relation recognition datasets and methods aiming to help researchers to have a better understanding of the char- acteristics of the state-of-the-art. In the proposed study, we distinguish between methods that address objective relations that...