Paheding Sidike

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 6 papers; trusts 187 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 261 citations into it
• Computer Vision and Pattern Recognition — 245 citations into it
• Model Architectures — 91 citations into it
• Optimization & Training — 44 citations into it
• Representation & Self-Supervised Learning — 33 citations into it
• Probabilistic & Bayesian Methods — 14 citations into it
• Control and Systems Engineering — 8 citations into it

Whom Paheding Sidike trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Kaiming He
5. Yann LeCun
6. Ilya Sutskever
7. Diederik P. Kingma
8. Christian Szegedy
9. Alex Graves
10. J. Urgen Schmidhuber

Who trusts Paheding Sidike overall

1. Md. Zahangir Alom

Papers from Paheding Sidike's perspective

Ordered by how strongly the researchers Paheding Sidike trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Monitoring inland water quality using remote sensing: potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing (2020) — 542 citations
• Soybean yield prediction from UAV using multimodal data fusion and deep learning (2020) — 852 citations
• A State-of-the-Art Survey on Deep Learning Theory and Architectures (2019) — 1,450 citations
• Vegetation Index Weighted Canopy Volume Model (CVMVI) for soybean biomass estimation from Unmanned Aerial System-based RGB imagery (2019) — 227 citations
• The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches (2018) — 1,014 citations
• Unmanned Aerial System (UAS)-Based Phenotyping of Soybean using Multi-sensor Data Fusion and Extreme Learning Machine (2017) — 339 citations