Priyanka Raina

Computer Vision and Pattern Recognition · 2019–2022

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 58 citations into it

Whom Priyanka Raina trusts overall

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

1. Alex Krizhevsky
2. Yu-hsin Chen

Papers from Priyanka Raina's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Going deeper with convolutions
3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. Learning Multiple Layers of Features from Tiny Images
5. Attention is All you Need (Neural Information Processing Systems)
6. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet classification with deep convolutional neural networks
9. Caffe: Convolutional Architecture for Fast Feature Embedding
10. Fully convolutional networks for semantic segmentation

Their papers

• Timeloop: A Systematic Approach to DNN Accelerator Evaluation (2019) — 671 citations
• Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture (2019) — 495 citations
• A compute-in-memory chip based on resistive random-access memory (2022) — 863 citations