paper-with-me

Papers

Cubic Spline Interpolation Segmenting over Conventional Segmentation Procedures: Application and Advantages

2018-03-13

To design a novel method for segmenting the image using Cubic Spline Interpolation and compare it with different techniques to determine which gives an efficient data to segment an image. This paper compares polynomial least square interpolation and the conventional Otsu thresholding with spline interpolation technique for image segmentation. The threshold value is determined using the above-mentioned techniques which are then used to segment an image into the binary image. The results of the proposed technique are also compared with the conventional algorithms after applying image equalizations. The better technique is determined based on the deviation and mean square error when compared with an accurately segmented image. The image with least amount of deviation and mean square error is declared as the better technique.

📄 PDF Abstract BibTeX arXiv:1803.04621

Code (0)

등록된 구현이 없습니다.

Tasks

Image SegmentationSemantic Segmentation

Similar Papers 제목 키워드 기반

Cubic Spline Smoothing Compensation for Irregularly Sampled Sequences

2020-10-03 · Jing Shi, Jing Bi, Yingru Liu, Chenliang Xu

The marriage of recurrent neural networks and neural ordinary differential networks (ODE-RNN) is effective in modeling irregularly-observed sequences. While ODE produces the smooth hidden states between observation inter…

Application Research of Spline Interpolation and ARIMA in the Field of Stock Market Forecasting

2023-11-14 · Xitai Yu

The ARIMA (Autoregressive Integrated Moving Average model) has extensive applications in the field of time series forecasting. However, the predictive performance of the ARIMA model is limited when dealing with data gaps…

Time SeriesTime Series Forecasting

Deep Learning-Driven Prediction of Microstructure Evolution via Latent Space Interpolation

2025-08-03 · Sachin Gaikwad, Thejas Kasilingam, Owais Ahmad, Rajdip Mukherjee 외 arxiv

Phase-field models accurately simulate microstructure evolution, but their dependence on solving complex differential equations makes them computationally expensive. This work achieves a significant acceleration via a no…

Rendering Novel Views of MRI Using 3D Gaussian Splatting

2026-06-24 · Robin Y. Park, Mark C. Eid, Rhydian Windsor, Amir Jamaludin 외 arxiv

The objective of this paper is to improve radiological gradings measured on MRIs of spines, by resampling scans so that the new view planes are better aligned with the target anatomy than the original sparse images. To t…

Learning activation functions from data using cubic spline interpolation

2016-05-18 · Simone Scardapane, Michele Scarpiniti, Danilo Comminiello, Aurelio Uncini

Neural networks require a careful design in order to perform properly on a given task. In particular, selecting a good activation function (possibly in a data-dependent fashion) is a crucial step, which remains an open p…