mlsanityData to 7 Oct 2026

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

arXiv 2205.12775 ↗First posted 25 May 2022cs.LGcited by 2

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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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 30 references that are in the map. First posted on arXiv 25 May 2022.

Builds on

14 of 30 references.

References · 14

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  4. 2015Highway Networkscited by 257
  5. 2020Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNetscited by 165
  6. 2018Activation Functions: Comparison of trends in Practice and Research for Deep Learningcited by 130
  7. 2018A high-bias, low-variance introduction to Machine Learning for physicistscited by 108
  8. 2021On the approximation of functions by tanh neural networkscited by 81
  9. 2019Deep Compressed Sensingcited by 46
  10. 2020On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspectivecited by 25
  11. 2022Succinct Differentiation of Disparate Boosting Ensemble Learning Methods for Prognostication of Polycystic Ovary Syndrome Diagnosiscited by 9
  12. 2022Discriminant Analysis in Contrasting Dimensions for Polycystic Ovary Syndrome Prognosticationcited by 9
2 more
  1. 2022Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Methodcited by 8
  2. 2022Combining Varied Learners for Binary Classification using Stacked Generalizationcited by 4

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Cited by year

Citing papers per year: 2022: 1; 2023: 1.

2 papers.

  1. 2022Forged Image Detection using SOTA Image Classification Deep Learning Methods for Image Forensics with Error Level Analysiscited by 1
  2. 2023Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classificationcited by 0