# Recent Advances in Deep Learning: An Overview

arXiv: https://arxiv.org/abs/1807.08169 · HTML: https://mlsanity.com/paper/1807.08169/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jul 2018.

## Built on by (most cited first, 10 of 10)

- [Student Network Learning via Evolutionary Knowledge Distillation](https://mlsanity.com/paper/2103.13811/) (2021)
- [Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design](https://mlsanity.com/paper/2207.10330/) (2022)
- [LuSNAR:A Lunar Segmentation, Navigation and Reconstruction Dataset based on Muti-sensor for Autonomous Exploration](https://mlsanity.com/paper/2407.06512/) (2024)
- [A novel DL approach to PE malware detection: exploring Glove vectorization, MCC_RCNN and feature fusion](https://mlsanity.com/paper/2101.08969/) (2021)
- [Noisy Truncated SGD: Optimization and Generalization](https://mlsanity.com/paper/2103.00075/) (2021)
- [Early Melanoma Diagnosis with Sequential Dermoscopic Images](https://mlsanity.com/paper/2110.05976/) (2021)
- [Artificial Satellite Trails Detection Using U-Net Deep Neural Network and Line Segment Detector Algorithm](https://mlsanity.com/paper/2509.16771/) (2025)
- [Characterization of Neural Networks Automatically Mapped on Automotive-grade Microcontrollers](https://mlsanity.com/paper/2103.00201/) (2021)
- [Knowing the Past to Predict the Future: Reinforcement Virtual Learning](https://mlsanity.com/paper/2211.01266/) (2022)
- [Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization](https://mlsanity.com/paper/2408.06212/) (2024)

## Abstract (arXiv)

Deep Learning is one of the newest trends in Machine Learning and Artificial Intelligence research. It is also one of the most popular scientific research trends now-a-days. Deep learning methods have brought revolutionary advances in computer vision and machine learning. Every now and then, new and new deep learning techniques are being born, outperforming state-of-the-art machine learning and even existing deep learning techniques. In recent years, the world has seen many major breakthroughs in this field. Since deep learning is evolving at a huge speed, its kind of hard to keep track of the regular advances especially for new researchers. In this paper, we are going to briefly discuss about recent advances in Deep Learning for past few years.