Classifying three dimensional shapes and making connectionsBerkeley Electronic Press Selected WorksJessica H. HuntE. S. Haciomeroglu
CNNs also recently became the leading technique for both 2-dimensional and 3-dimensional human pose estimation, where the goal is to estimate the positions of several "key" joints such as shoulders, elbows, and wrists16–20. While CNNs could hence likely improve body part detection in ...
We classify distinct types of quantum number fractionalization occurring in two-dimensional topologically ordered phases, focusing in particular on phases ... AM Essin,M Hermele - 《Physical Review B》 被引量: 24发表: 2013年 Classifying symmetry-protected topological phases through the anomalous action...
Classify two-dimensional figures based on the presence or absence of parallel or perpendicular lines, or the presence or absence of angles of a specified size. Recognize right triangles as a category, and identify right triangles. Reviews 5.0Based on 47 reviews Ratings 5 stars 44 4 stars 3 3...
A new method for the recognition of arbitrary two-dimensional (2D) shapes is described. It is based on string edit distance computation. The recognition me... H Bunke,U Bühler - 《Pattern Recognition》 被引量: 313发表: 1993年 Device and method for pattern recognition A method of and appa...
34Citations 6Altmetric Metrics Abstract High-throughput analysis of animal behavior requires software to analyze videos. Such software analyzes each frame individually, detecting animals’ body parts. But the image analysis rarely attempts to recognize “behavioral states”—e.g., actions or facial expr...
3) A quadrilateral with two pairs of parallel sides. 4) A parallelogram with four congruent sides. 5) A rhombus with four right angles. 6) A parallelogram with four congruent sides and four congruent angles. A parallelogram is ___ a rectangle. Always, Sometimes, or Never A parallelogram...
The underlying work has two parts: the first part deals with pixel-based supervised LCZ classification incorporating contextual information for 90 m resolution to handle spatial heterogeneity, and the second part is the post-classification clustering approach based on spatial cohesion to obtain ...
An artificial neural network for classifying cross peaks in two-dimensional NMR spectra. J. Magn. Reson. 1992; 100 :256–266.Corne S A, Johnson P. An artificial neural network for classi- fying cross peaks in two-dimensional NMR spectra. Journal of Magnetic Resonance, 1992, 100(2): 256-...
Classifying three dimensional shapes and making connectionsBerkeley Electronic Press Selected WorksDimensionsHunt, Jessica HHaciomeroglu, E. S