The DOI matches its Crossref record.
Deep Learning: Foundations and Concepts
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“They support detecting and classifying individuals even with background noise or occlusions.”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [52]
In the citing paper
“Combined with CNNs [52] or other classifiers, background subtraction can improve accuracy by reducing the false positives of nonpassenger objects.”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [52]
Citations
Cites
Still being checked.
Cited by
Sorted by citations
Bewersdorff, A., Hornberger, M., Nerdel, C., & Schiff, D. S. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100340 · Cited by 148
Transformers and genome language models
Consens, M. E., Dufault, C., Wainberg, M., Forster, D., Karimzadeh, M., Goodarzi, H., Theis, F. J., Moses, A. M., & Wang, B. (2025) · Nature Machine Intelligence · doi:10.1038/s42256-025-01007-9 · Cited by 170
Physics-driven learning for inverse problems in quantum chromodynamics
Gert Aarts, A., Fukushima, K., Hatsuda, T., Ipp, A., Shi, S., Wang, L., & Zhou, K. (2025) · Nature Reviews Physics · doi:10.1038/s42254-024-00798-x · Cited by 64
Gemechu, W. F., Sitek, W., & Batalha, G. F. (2024) · Applied Sciences · doi:10.3390/app14062554 · Cited by 30
Fractional Calculus Meets Neural Networks for Computer Vision: A Survey
Coelho, C., Costa, M. F. P., & Ferrás, L. L. (2024) · AI · doi:10.3390/ai5030067 · Cited by 31
Metadata
- Authors
- Bishop, C. M., & Bishop, H.
- Venue
- Springer eBooks
- Publisher
- Springer International Publishing
- Published
- 2024
- OpenAlex
- W4388152645
- Cited by
- 220
- References
- 0
- Citations by year
- 2026: 81 · 2025: 92 · 2024: 47
- FWCI
- 38.61
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- deep learning, deep learning architectures, artificial neural networks, machine learning methods
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
