# Residual-Concatenate Neural Network with Deep Regularization Layers for Binary Classification

arXiv: https://arxiv.org/abs/2205.12775 · HTML: https://mlsanity.com/paper/2205.12775/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 30 references that are in the map.
- First posted on arXiv 25 May 2022.

## Builds on (most cited first, 14 of 14)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Highway Networks](https://mlsanity.com/paper/1505.00387/) (2015)
- [Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets](https://mlsanity.com/paper/2002.05990/) (2020)
- [Activation Functions: Comparison of trends in Practice and Research for Deep Learning](https://mlsanity.com/paper/1811.03378/) (2018)
- [A high-bias, low-variance introduction to Machine Learning for physicists](https://mlsanity.com/paper/1803.08823/) (2018)
- [On the approximation of functions by tanh neural networks](https://mlsanity.com/paper/2104.08938/) (2021)
- [Deep Compressed Sensing](https://mlsanity.com/paper/1905.06723/) (2019)
- [On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective](https://mlsanity.com/paper/2011.11152/) (2020)
- [Succinct Differentiation of Disparate Boosting Ensemble Learning Methods for Prognostication of Polycystic Ovary Syndrome Diagnosis](https://mlsanity.com/paper/2201.00418/) (2022)
- [Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognostication](https://mlsanity.com/paper/2201.03029/) (2022)
- [Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Method](https://mlsanity.com/paper/2202.07779/) (2022)
- [Combining Varied Learners for Binary Classification using Stacked Generalization](https://mlsanity.com/paper/2202.08910/) (2022)

## Built on by (most cited first, 2 of 2)

- [Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysis](https://mlsanity.com/paper/2211.15196/) (2022)
- [Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification](https://mlsanity.com/paper/2303.14401/) (2023)

## Abstract (arXiv)

Many complex Deep Learning models are used with different variations for various prognostication tasks. The higher learning parameters not necessarily ensure great accuracy. This can be solved by considering changes in very deep models with many regularization based techniques. In this paper we train a deep neural network that uses many regularization layers with residual and concatenation process for best fit with Polycystic Ovary Syndrome Diagnosis prognostication. The network was built with improvements from every step of failure to meet the needs of the data and achieves an accuracy of 99.3% seamlessly.