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**A Survey on Bayesian Deep Learning**,

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Probabilistic logic, Artificial neural networks,
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IEEE DOI
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Deep learning, Training, Task analysis, Data models,
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**A Survey on Curriculum Learning**,

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IEEE DOI
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Training, Task analysis, Machine learning, Data models, Convergence,
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Task analysis, Optimization, Training, Machine learning algorithms,
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**Deep Generative Modelling: A Comparative Review of VAEs, GANs,
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*PAMI(44)*, No. 11, November 2022, pp. 7327-7347.

IEEE DOI
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*Survey, Generative Modeling*. Data models, Training, Computational modeling, Analytical models,
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**Investigating Bi-Level Optimization for Learning and Vision from a
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*PAMI(44)*, No. 12, December 2022, pp. 10045-10067.

IEEE DOI
**2212**

Optimization, Task analysis, Convergence, Complexity theory,
Reinforcement learning, Multitasking, Bi-level optimization,
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**A Systematic Survey of Regularization and Normalization in GANs**,

*Surveys(55)*, No. 11, February 2023, pp. xx-yy.

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Training Dynamics, Generative Adversarial Networks, Lipschitz Neural networks
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**Untrained Neural Network Priors for Inverse Imaging Problems:
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*PAMI(45)*, No. 5, May 2023, pp. 6511-6536.

IEEE DOI
**2304**

Inverse problems, Neural networks, Imaging, Task analysis,
Image reconstruction, Noise measurement, Deep learning,
deep learning
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*Peng, S.Y.[Si-Yuan]*,
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**Adaptive graph regularization method based on least square regression
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*SP:IC(114)*, 2023, pp. 116938.

Elsevier DOI
**2305**

Adaptive graph regularization, Least squares regression,
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*Stankovic, L.[Ljubiša]*,
*Mandic, D.[Danilo]*,

**Convolutional Neural Networks Demystified:
A Matched Filtering Perspective-Based Tutorial**,

*SMCS(53)*, No. 6, June 2023, pp. 3614-3628.

IEEE DOI
**2305**

Convolution, Noise measurement, Pattern matching,
Feature extraction, Standards, Signal resolution, Filtering,
matched filter
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*Huang, Y.[Yangsibo]*,
*Huang, C.Y.[Chun-Yin]*,
*Li, X.X.[Xiao-Xiao]*,
*Li, K.[Kai]*,

**A Dataset Auditing Method for Collaboratively Trained Machine
Learning Models**,

*MedImg(42)*, No. 7, July 2023, pp. 2081-2090.

IEEE DOI
**2307**

Data models, Training, Regulation, Calibration, Analytical models,
Measurement, Robustness, Privacy, dataset auditing, medical image classification
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*Obukhov, T.[Timur]*,
*Brovelli, M.A.[Maria A.]*,

**Identifying Conditioning Factors and Predictors of Conflict
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*IJGI(12)*, No. 8, 2023, pp. 322.

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*Zhang, Q.[Qi]*,
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**Efficient High-Resolution Deep Learning: A Survey**,

*Surveys(56)*, No. 7, April 2024, pp. xx-yy.

DOI Link
**2405**

*Survey, Deep Learning*. High-resolution deep learning, efficient deep learning, vision transformer
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*Akar, C.A.[Chafic Abou]*,
*Massih, R.A.[Rachelle Abdel]*,
*Yaghi, A.[Anthony]*,
*Khalil, J.[Joe]*,
*Kamradt, M.[Marc]*,
*Makhoul, A.[Abdallah]*,

**Generative Adversarial Network Applications in Industry 4.0: A Review**,

*IJCV(132)*, No. 6, June 2024, pp. 2195-2254.

Springer DOI
**2406**

BibRef

*Mettes, P.[Pascal]*,
*Atigh, M.G.[Mina Ghadimi]*,
*Keller-Ressel, M.[Martin]*,
*Gu, J.[Jeffrey]*,
*Yeung, S.[Serena]*,

**Hyperbolic Deep Learning in Computer Vision: A Survey**,

*IJCV(132)*, No. 1, January 2024, pp. 3484-3508.

Springer DOI
**2409**

*Deep Learning*.
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*Warner, E.[Elisa]*,
*Lee, J.[Joonsang]*,
*Hsu, W.[William]*,
*Syeda-Mahmood, T.[Tanveer]*,
*Kahn Jr., C.E.[Charles E.]*,
*Gevaert, O.[Olivier]*,
*Rao, A.[Arvind]*,

**Multimodal Machine Learning in Image-Based and Clinical Biomedicine:
Survey and Prospects**,

*IJCV(132)*, No. 1, January 2024, pp. 3753-3769.

Springer DOI
**2409**

BibRef

IEEE DOI

Privacy, Computational modeling, Estimation, Probability, Data models, Faces, Algorithms, Explainable, fair, accountable, ethical computer vision BibRef

*Ganesh, P.[Prakhar]*,

**An Empirical Investigation into Benchmarking Model Multiplicity for
Trustworthy Machine Learning: A Case Study on Image Classification**,

*WACV24*(4476-4485)

IEEE DOI
**2404**

Measurement, Deep learning, Computational modeling,
Benchmark testing, Market research, Image classification,
Social good
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*Pathak, A.[Abha]*,
*Arya, K.V.[Karm Veer]*,
*Tiwari, V.[Vivek]*,
*Bhende, M.[Manisha]*,

**Unveiling Image Classifiers:
An In-Depth Comparative Exploration of Machine Learning Algorithms**,

*ICCVMI23*(1-5)

IEEE DOI
**2403**

Support vector machines, Machine learning algorithms, Navigation,
Heuristic algorithms, Classification algorithms,
Content Moderation
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*Wang, Q.Y.[Qing-Yang]*,
*Powell, M.A.[Michael A.]*,
*Geisa, A.[Ali]*,
*Bridgeford, E.[Eric]*,
*Priebe, C.E.[Carey E.]*,
*Vogelstein, J.T.[Joshua T.]*,

**Why do networks have inhibitory/negative connections?**,

*ICCV23*(22494-22502)

IEEE DOI
**2401**

BibRef

*Hanspal, H.[Harleen]*,
*Lomuscio, A.[Alessio]*,

**Efficient Verification of Neural Networks Against LVM-Based
Specifications**,

*CVPR23*(3894-3903)

IEEE DOI
**2309**

BibRef

*Matzinger, H.[Heinrich]*,
*Allgeier, A.[Allegra]*,

**CNN Image Recognition is Mainly Based on Local Features**,

*ICRVC22*(90-95)

IEEE DOI
**2301**

Image recognition, Shape, Robot sensing systems,
Pattern recognition, Convolutional neural networks,
artificial intelligence
BibRef

*Alfarra, M.[Motasem]*,
*Pérez, J.C.[Juan C.]*,
*Frühstück, A.[Anna]*,
*Torr, P.H.S.[Philip H. S.]*,
*Wonka, P.[Peter]*,
*Ghanem, B.[Bernard]*,

**On the Robustness of Quality Measures for GANs**,

*ECCV22*(XVII:18-33).

Springer DOI
**2211**

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*Gavrikov, P.[Paul]*,
*Keuper, J.[Janis]*,

**CNN Filter DB:
An Empirical Investigation of Trained Convolutional Filters**,

*CVPR22*(19044-19054)

IEEE DOI
**2210**

WWW Link. Convolution, Computational modeling,
Information filters, Robustness, Entropy, Datasets and evaluation,
Transfer/low-shot/long-tail learning
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*Gavrikov, P.[Paul]*,
*Keuper, J.[Janis]*,

**Adversarial Robustness through the Lens of Convolutional Filters**,

*ArtOfRobust22*(138-146)

IEEE DOI
**2210**

Training, Convolution, Perturbation methods,
Predictive models, Robustness, Data models
BibRef

*Inkawhich, M.[Matthew]*,
*Inkawhich, N.[Nathan]*,
*Davis, E.[Eric]*,
*Li, H.[Hai]*,
*Chen, Y.[Yiran]*,

**The Untapped Potential of Off-the-Shelf Convolutional Neural Networks**,

*WACV22*(2907-2916)

IEEE DOI
**2202**

Training, Upper bound, Convolution,
Network architecture, Inference algorithms, Data models,
Vision Systems and Applications
BibRef

*Minskiy, D.[Dmitry]*,
*Bober, M.[Miroslaw]*,

**Efficient Hybrid Network: Inducting Scattering Features**,

*ICPR22*(2300-2306)

IEEE DOI
**2212**

BibRef

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**Scattering-Based Hybrid Networks: An Evaluation and Design Guide**,

*ICIP21*(2793-2797)

IEEE DOI
**2201**

Training, Force, Scattering, Training data, Performance gain,
Stability analysis.
Image resolution, System performance, Buildings, hybrid, network design
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*Zhou, H.Y.[Hong-Yu]*,
*Lu, C.X.[Chi-Xiang]*,
*Yang, S.[Sibei]*,
*Yu, Y.Z.[Yi-Zhou]*,

**ConvNets vs. Transformers:
Whose Visual Representations are More Transferable?**,

*DeepMTL21*(2230-2238)

IEEE DOI
**2112**

Performance evaluation, Visualization,
Face recognition, Transfer learning, Estimation
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*Wang, X.H.[Xiao-Han]*,
*Eliott, F.M.[Fernanda M.]*,
*Ainooson, J.[James]*,
*Palmer, J.H.[Joshua H.]*,
*Kunda, M.[Maithilee]*,

**An Object is Worth Six Thousand Pictures:
The Egocentric, Manual, Multi-image (EMMI) Dataset**,

*Egocentric17*(2364-2372)

IEEE DOI

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**1802**

*Dataset, Learning*. Egocentric, Manual, Multi-Image (EMMI) Dataset.
Automobiles, Cameras, Manuals, Object recognition,
Toy manufacturing industry, Training, Visualization
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**The Prax Approach to Learning a Large Number of
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*AAAI-MLCV93*(xx-yy).
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**Progress on Vision through Learning at George Mason University**,

*ARPA94*(I:191-207).
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**Progress on Vision Through Learning**,

*ARPA96*(177-188).
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**Report of the AAAI Fall Symposium on Machine Learning and
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*ARPA94*(I:727-731).
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in

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