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Some Improvements on Deep Convolutional Neural Network Based Image Classification

arXiv 1312.5402 ↗First posted 19 Dec 2013cs.CVcited by 34

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Abstract (arXiv)

We investigate multiple techniques to improve upon the current state of the art deep convolutional neural network based image classification pipeline. The techiques include adding more image transformations to training data, adding more transformations to generate additional predictions at test time and using complementary models applied to higher resolution images. This paper summarizes our entry in the Imagenet Large Scale Visual Recognition Challenge 2013. Our system achieved a top 5 classification error rate of 13.55% using no external data which is over a 20% relative improvement on the previous year's winner.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Dec 2013.

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Citing papers per year: 2021: 10; 2022: 14; 2023: 5; 2024: 3; 2025: 1; 2026: 1.

34 papers.

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  10. 2022On the Origins of the Block Structure Phenomenon in Neural Network Representationscited by 10
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22 more
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  5. 2022MobileDenseNet: A new approach to object detection on mobile devicescited by 3
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  7. 2023Temporal Contrastive Learning for Spiking Neural Networkscited by 3
  8. 2026VLM-UQBench: A Benchmark for Modality-Specific and Cross-Modality Uncertainties in Vision Language Modelscited by 3
  9. 2021Adaptive Test-Time Augmentation for Low-Power CPUcited by 2
  10. 2022DU-Net based Unsupervised Contrastive Learning for Cancer Segmentation in Histology Imagescited by 1
  11. 2022Real-Time Cattle Interaction Recognition via Triple-stream Networkcited by 1
  12. 2021Geometric Data Augmentation Based on Feature Map Ensemblecited by 0
  13. 2022Enhanced Performance of Pre-Trained Networks by Matched Augmentation Distributionscited by 0
  14. 2022Vision-Based American Sign Language Classification Approach via Deep Learningcited by 0
  15. 2022Multi-Augmentation for Efficient Visual Representation Learning for Self-supervised Pre-trainingcited by 0
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  19. 2023Augmentation is AUtO-Net: Augmentation-Driven Contrastive Multiview Learning for Medical Image Segmentationcited by 0
  20. 2024Breaking The Ice: Video Segmentation for Close-Range Ice-Covered Waterscited by 0
  21. 2024Optimizing Data Curation through Spectral Analysis and Joint Batch Selection (SALN)cited by 0
  22. 2025Steganographic Embeddings as an Effective Data Augmentationcited by 0