ResNet or DenseNet? Introducing Dense Shortcuts to ResNet

Deep Residual Learning for Image Recognition

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ImageNet classification with deep convolutional neural networks

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

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ImageNet: A large-scale hierarchical image database

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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

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Distinctive Image Features from Scale-Invariant Keypoints

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Densely Connected Convolutional Networks

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Going deeper with convolutions

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Microsoft COCO: Common Objects in Context

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Fully convolutional networks for semantic segmentation

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Squeeze-and-Excitation Networks

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Histograms of Oriented Gradients for Human Detection

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Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

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Rethinking the Inception Architecture for Computer Vision

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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

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CBAM: Convolutional Block Attention Module

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Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

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Visualizing and understanding convolutional networks

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Layer NormalizationPreprint

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Aggregated Residual Transformations for Deep Neural Networks

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Identity mappings in deep residual networks

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Explaining and Harnessing Adversarial Examples

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Intriguing properties of neural networks

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Wide Residual Networks

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Instance Normalization: The Missing Ingredient for Fast StylizationPreprint

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Group Normalization

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Striving for Simplicity: The All Convolutional Net

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Res2Net: A New Multi-Scale Backbone Architecture

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Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural NetworksPreprint

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Deep Networks with Stochastic Depth

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Understanding deep image representations by inverting them

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How Does Batch Normalization Help Optimization? (No, It Is Not About Internal Covariate Shift)Preprint

Santurkar, S., Tsipras, D., Ilyas, A., & Ma̧dry, A. (2018) · Neural Information Processing Systems · doi:10.48550/arxiv.1805.11604 · Cited by 1,788 · see citing works

Deeply-Supervised NetsPreprint

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Highway Networks

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CondenseNet: An Efficient DenseNet Using Learned Group Convolutions

Huang, G., Liu, S., Maaten, L. V. D., & Weinberger, K. Q. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00291 · Cited by 904 · see citing works

FractalNet: Ultra-Deep Neural Networks without ResidualsPreprint

Larsson, G., Maire, M., & Shakhnarovich, G. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.07648 · Cited by 810 · see citing works

Dual Path NetworksPreprint

Chen, Y., Li, J., Xiao, H., Jin, X., Yan, S., & Feng, J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.01629 · Cited by 714 · see citing works

Weight normalization: a simple reparameterization to accelerate training of deep neural networks

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Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision

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Interleaved Group Convolutions

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FractalNet: Ultra-Deep Neural Networks without Residuals.

Larsson, G., Maire, M., & Shakhnarovich, G. (2017) · International Conference on Learning Representations · Cited by 315 · see citing works

Video Panoptic Segmentation

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Understanding Adversarial Examples From the Mutual Influence of Images and Perturbations

Zhang, C., Benz, P., Imtiaz, T., & Kweon, I. S. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01453 · Cited by 144 · see citing works

Memory-Efficient Implementation of DenseNetsPreprint

Pleiss, G., Chen, D., Huang, G. M., Li, T., van der Maaten, L., & Weinberger, K. Q. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.06990 · Cited by 129 · see citing works

Revisiting Internal Covariate Shift for Batch Normalization

Awais, M., Iqbal, M. T. B., & Bae, S. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3026784 · Cited by 95 · see citing works

Targeted Attack for Deep Hashing Based Retrieval

Bai, J., Chen, B., Li, Y., Wu, D., Guo, W., Xia, S., & Yang, E. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58452-8_36 · Cited by 86 · see citing works

Recurrent Temporal Aggregation Framework for Deep Video Inpainting

Kim, D., Woo, S., Lee, J., & Kweon, I. S. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2958083 · Cited by 71 · see citing works

Revisiting Batch Normalization for Improving Corruption Robustness

Benz, P., Zhang, C., Karjauv, A., & Kweon, I. S. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00054 · Cited by 66 · see citing works

CD-UAP: Class Discriminative Universal Adversarial Perturbation

Zhang, C., Benz, P., Imtiaz, T., & Kweon, I.-S. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i04.6154 · Cited by 55 · see citing works

Mixed Link Networks

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Double Targeted Universal Adversarial Perturbations

Benz, P., Zhang, C., Imtiaz, T., & Kweon, I. S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-69538-5_18 · Cited by 52 · see citing works

DeepPTZ: Deep Self-Calibration for PTZ Cameras

Zhang, C., Rameau, F., Kim, J., Argaw, D. M., Bazin, J., & Kweon, I. S. (2020) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv45572.2020.9093629 · Cited by 47 · see citing works

Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-SupervisionPreprint

Pan, F., Shin, I., Rameau, F., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.07703 · Cited by 40 · see citing works

Adversarial Attack on Deep Product Quantization Network for Image Retrieval

Feng, Y., Chen, B., Dai, T., & Xia, S. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6708 · Cited by 39 · see citing works

Gradients explode - Deep Networks are shallow - ResNet explainedPreprint

Philipp, G., Song, D. X., & Carbonell, J. (2017) · arXiv (Cornell University) · Cited by 34 · see citing works

Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise AccuracyPreprint

Benz, P., Zhang, C., Karjauv, A., & Kweon, I. S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.13365 · Cited by 32 · see citing works

Revisiting Residual Networks with Nonlinear Shortcuts.

Zhang, C., Rameau, F., Lee, S., Kim, J., Benz, P., Argaw, D. M., Bazin, J., & Kweon, I. S. (2019) · KAIST Institutional Repository (KAIST) · Cited by 27 · see citing works

The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation

Kim, M., Woo, S., Kim, D., & Kweon, I. S. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00097 · Cited by 21 · see citing works

Towards an Adversarially Robust Normalization ApproachPreprint

Awais, M., Shamshad, F., & Bae, S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.11007 · Cited by 18 · see citing works

Intriguing properties of adversarial training at scalePreprint

Xie, C., & Yuille, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.03787 · Cited by 16 · see citing works

Data from Model: Extracting Data from Non-robust and Robust ModelsPreprint

Benz, P., Zhang, C., Imtiaz, T., & Kweon, I.-S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.06196 · Cited by 8 · see citing works

Batch Normalization Increases Adversarial Vulnerability: Disentangling Usefulness and Robustness of Model FeaturesPreprint

Benz, P., Zhang, C., & Kweon, I. S. (2021) · arXiv (Cornell University) · Cited by 8 · see citing works

Understanding Adversarial Examples from the Mutual Influence of Images and PerturbationsPreprint

Zhang, C., Benz, P., Imtiaz, T., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.06189 · Cited by 4 · see citing works

A Comprehensive Review of Convolutional Neural Networks for Defect Detection in Industrial Applications

Khanam, R., Hussain, M., Hill, R. C., & Allen, P. (2024) · IEEE Access · doi:10.1109/access.2024.3425166 · Cited by 273 · see citing works

A Comprehensive Survey of Deep Learning Approaches in Image Processing

Τρίγκα, Μ., & Dritsas, E. (2025) · Sensors · doi:10.3390/s25020531 · Cited by 159 · see citing works

Optimization and fine-tuning of DenseNet model for classification of COVID-19 cases in medical imaging

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Eye Know You Too: Toward Viable End-to-End Eye Movement Biometrics for User Authentication

Lohr, D. J., & Komogortsev, O. V. (2022) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2022.3201369 · Cited by 90 · see citing works

Classification of Breast Cancer Histopathological Images Using DenseNet and Transfer Learning

Wakili, M. A., Shehu, H. A., Sharif, M. H., Sharif, M. H. U., Umar, A., Kusetoğulları, H., İnce, İ. F., & Uyaver, Ş. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/8904768 · Cited by 88 · see citing works

Delamination detection in CFRP laminates using deep transfer learning with limited experimental data

Azad, M. M., Kumar, P., & Kim, H. S. (2024) · Journal of Materials Research and Technology · doi:10.1016/j.jmrt.2024.02.067 · Cited by 64 · see citing works

Revisiting Batch Normalization for Improving Corruption Robustness

Benz, P., Zhang, C., Karjauv, A., & Kweon, I. S. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00054 · Cited by 66 · see citing works

Deep Learning for Improving the Effectiveness of Routine Prenatal Screening for Major Congenital Heart Diseases

Nurmaini, S., Partan, R. U., Bernolian, N., Sapitri, A. I., Tutuko, B., Rachmatullah, M. N., Darmawahyuni, A., Firdaus, F., & Mose, J. C. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11216454 · Cited by 61 · see citing works

Four Types of Multiclass Frameworks for Pneumonia Classification and Its Validation in X-ray Scans Using Seven Types of Deep Learning Artificial Intelligence Models

Nillmani, Jain, P. K., Sharma, N., Kalra, M. M., Višković, K., Saba, L., & Suri, J. S. (2022) · Diagnostics · doi:10.3390/diagnostics12030652 · Cited by 65 · see citing works

Depth-Wise Separable Convolution Attention Module for Garbage Image Classification

Liu, F., Xu, H. F., Qi, M., Liu, D., Wang, J., & Kong, J. (2022) · Sustainability · doi:10.3390/su14053099 · Cited by 56 · see citing works

Brightness as an Augmentation Technique for Image Classification

Kandel, I., Castelli, M., & Manzoni, L. (2022) · Emerging Science Journal · doi:10.28991/esj-2022-06-04-015 · Cited by 55 · see citing works

Acoustic-Based Deep Learning Architectures for Lung Disease Diagnosis: A Comprehensive Overview

Sfayyih, A. H., Sabry, A. H., Jameel, S. M., Sulaiman, N., Raafat, S. M., Humaidi, A. J., & Alkubaisi, Y. M. (2023) · Diagnostics · doi:10.3390/diagnostics13101748 · Cited by 52 · see citing works

DenseNet-ABiLSTM: Revolutionizing Multiclass Arrhythmia Detection and Classification Using Hybrid Deep Learning Approach Leveraging PPG Signals

Saranya, K., Karthikeyan, U., Kumar, A., Salau, A. O., & Tin, T. T. (2025) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-025-00765-z · Cited by 51 · see citing works

GCCNet: A Novel Network Leveraging Gated Cross-Correlation for Multi-View Classification

Zeng, Y., Zhang, R., Zhang, H., Qiao, S., Huang, F., Tian, Q., & Peng, Y. (2024) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2024.3521733 · Cited by 47 · see citing works

Building use and mixed-use classification with a transformer-based network fusing satellite images and geospatial textual information

Zhou, W., Persello, C., Li, M., & Stein, A. (2023) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113767 · Cited by 46 · see citing works

Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards a Fourier Perspective

Zhang, C., Benz, P., Karjauv, A., & Kweon, I. S. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i4.16441 · Cited by 41 · see citing works

An Artificial Intelligence-Enabled ECG Algorithm for the Prediction and Localization of Angiography-Proven Coronary Artery Disease

Huang, P., Tseng, Y.-H., Tsai, C., Chen, J., Yang, S.-C., Chiu, F., Chen, Z., Hwang, J., Chuang, E. Y.-Y., Wang, Y., et al. (2022) · Biomedicines · doi:10.3390/biomedicines10020394 · Cited by 40 · see citing works

Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI

Palombo, M., Valindria, V. V., Singh, S., Chiou, E., Giganti, F., Pye, H., Whitaker, H. C., Atkinson, D., Punwani, S., Alexander, D. C., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-30182-1 · Cited by 39 · see citing works

DAST-Net: Dense visual attention augmented spatio-temporal network for unsupervised video anomaly detection

Kommanduri, R., & Ghorai, M. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127444 · Cited by 38 · see citing works

Classification method for folded flue-cured tobacco based on hyperspectral imaging and conventional neural networks

Wei, X., Deng, C. J., Fang, W., Xie, C., Liu, S., Lu, M., Wang, F., & Wang, Y. (2024) · Industrial Crops and Products · doi:10.1016/j.indcrop.2024.118279 · Cited by 35 · see citing works

A Comparative Analysis of Various Transfer Learning Approaches Skin Cancer Detection

Ashim, L. K., Suresh, N., & Prasannakumar, C. V. (2021) · International Conference on Trends in Electronics and Informatics (ICOEI) · doi:10.1109/icoei51242.2021.9452854 · Cited by 34 · see citing works

Generative Adversarial Network (GAN) for Automatic Reconstruction of the 3D Spine Structure by Using Simulated Bi-Planar X-ray Images

Yang, C.-J., Lin, C., Wang, C., Wang, J., Chen, R., Su, F., Lee, Y.-J., Lui, C., Yeh, L., & Fang, Y.-H. D. (2022) · Diagnostics · doi:10.3390/diagnostics12051121 · Cited by 34 · see citing works

Deep crowd anomaly detection: state-of-the-art, challenges, and future research directions

Sharif, M. H., Jiao, L., & Omlin, C. W. P. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-024-11092-8 · Cited by 37 · see citing works

Melanoma Skin Cancer Detection Using Recent Deep Learning Models

Guergueb, T., & Akhloufi, M. A. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9631047 · Cited by 29 · see citing works

Multimodal Deep Learning Integration of Image, Weather, and Phenotypic Data Under Temporal Effects for Early Prediction of Maize Yield

Shamsuddin, D., Danilevicz, M. F., Al-Mamun, H. A., Bennamoun, M., & Edwards, D. (2024) · Remote Sensing · doi:10.3390/rs16214043 · Cited by 29 · see citing works

Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications

Sun, J., Xu, M., Ru, J., James-Bott, A., Xiong, D., Wang, X., & Cribbs, A. P. (2023) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2023.115500 · Cited by 26 · see citing works

A deep convolutional neural network for the classification of imbalanced breast cancer dataset

Eshun, R. B., Bikdash, M. U., & Islam, A. K. M. K. (2024) · Healthcare Analytics · doi:10.1016/j.health.2024.100330 · Cited by 25 · see citing works

Universal Adversarial Training with Class-Wise Perturbations

Benz, P., Zhang, C., Karjauv, A., & Kweon, I. S. (2021) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme51207.2021.9428419 · Cited by 24 · see citing works

Parasitic egg recognition using convolution and attention network

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URNet: A U-Shaped Residual Network for Lightweight Image Super-Resolution

Wang, Y., Zhao, L. F., Liu, L., Hu, H., & Tao, W. (2021) · Remote Sensing · doi:10.3390/rs13193848 · Cited by 22 · see citing works

The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation

Kim, M., Woo, S., Kim, D., & Kweon, I. S. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00097 · Cited by 21 · see citing works

ViT-Based Multi-Scale Classification Using Digital Signal Processing and Image Transformation

Kim, G.-I., & Chung, K. (2024) · IEEE Access · doi:10.1109/access.2024.3389808 · Cited by 20 · see citing works

Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness

Zhang, C., Zhang, C., Zhang, C., Niu, A., Feng, J., Yoo, C. D., & Kweon, I. S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20056-4_42 · Cited by 18 · see citing works

YOLF-ShipPnet: Improved RetinaNet with Pyramid Vision Transformer

Qiu, Z.-R., Rong, S.-Y., & Ye, L.-K. (2023) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-023-00235-4 · Cited by 14 · see citing works

A framework for robotic arm pose estimation and movement prediction based on deep and extreme learning models

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MSF-YOLO: A multi-scale features fusion-based method for small object detection

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Artificial intelligence and dental age estimation: development and validation of an automated stage allocation technique on all mandibular tooth types in panoramic radiographs

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A Comprehensive Performance Analysis of Transfer Learning Optimization in Visual Field Defect Classification

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System identification methods for dynamic models of brain activity

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FedDebug: Systematic Debugging for Federated Learning Applications

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Detection of diabetic retinopathy and age-related macular degeneration using DenseNet based neural networks

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Cross-domain gesture recognition via WiFi signals with deep learning

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Comparison of residual and dense neural network approaches for building extraction from high-resolution aerial images

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PulmonNet V1: Leveraging the benefit of Leaky ReLU activation for the local and multi-scale global feature integration of chest radiographs to classify pulmonary diseases

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Depression detection in read and spontaneous speech: A Multimodal approach for lesser-resourced languages

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Self-Supervised Monocular Depth and Motion Learning in Dynamic Scenes: Semantic Prior to Rescue

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Boosting Online Feature Transfer via Separable Feature Fusion

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Bias Detection and Generalization in AI Algorithms on Edge for Autonomous Driving

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Identify Hard-to-Place Kidneys for Early Engagement in Accelerated Placement With a Deep Learning Optimization Approach

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Enhancing music audio signal recognition through CNN-BiLSTM fusion with De-noising autoencoder for improved performance

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Activity Recognition in Smart Homes via Feature-Rich Visual Extraction of Locomotion Traces

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A Multi-stage Deep Model for Crop Variety and Disease Prediction

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Deep Learning Methods for Bug Bite Classification: An End-to-End System

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Covid-19 and Pneumonia Infection Detection from Chest X-Ray Images using U-Net, EfficientNetB1, XGBoost and Recursive Feature Elimination

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Efficient deep-narrow residual networks using dilated pooling for scene recognition

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Real-Time Audio-Visual End-To-End Speech Enhancement

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A Siamese ResNeXt network for predicting carotid intimal thickness of patients with T2DM from fundus images

Gong, A., Fu, W., Li, H., Guo, N., & Pan, T. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1364519 · Cited by 8 · see citing works

Convolutional Neural Networks for Omnidirectional Image Quality Assessment: A Benchmark

Sendjasni, A., Larabi, M., & Cheikh, F. A. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3181235 · Cited by 8 · see citing works

MMO-Net (Multi-Magnification Organ Network): A use case for Organ Identification using Multiple Magnifications in Preclinical Pathology Studies

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A Deep Learning-Based No-Reference Quality Metric for High-Definition Images Compressed With HEVC

Xiang, J., Tohidypour, H. R., Wang, Y., Nasiopoulos, P., & Pourazad, M. T. (2023) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2023.3277193 · Cited by 8 · see citing works

Pre-trained Language Models

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Adaptive Learning Model for Detecting Wheat Diseases

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A high-precision spatial and spectral imaging solution for accurate corn nitrogen content level prediction at early vegetative growth stages

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A Hybrid Deep Transfer Learning Framework for Delamination Identification in Composite Laminates

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Transforming pulmonary health care: the role of artificial intelligence in diagnosis and treatment

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Transformer-based and CNN-based models for clinically effective 2D and 3D pelvic bone segmentation in CT imaging

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Artificial Intelligence of Behavior for Human Emotion Recognition in Closed Environments

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Lightweight Pedestrian Detection Based on Feature Multiplexed Residual Network

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Promoting accuracy in low-magnification histopathology grading: With augmentation and multi-dilation model

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Covidense: Providing a Suitable Solution for Diagnosing Covid-19 Lung Infection Based on Deep Learning from Chest X-Ray Images of Patients

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Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency

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Federated transfer learning for distributed drought stage prediction

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Multi‐scale nested graph transformer with graph operations: Advancing high‐resolution chest x‐ray classification

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Robust Watermarking for Neural Network Models Using Residual Network

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Visualizing Portable Executable Headers for Ransomware Detection: A Deep Learning-Based Approach

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Detection and classification of Brandt’s vole burrow clusters utilizing GF-2 satellite imagery and faster R-CNN model

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RACH Traffic Prediction in Massive Machine Type Communications

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Unmanned Aerial Multi-Object Dynamic Frame Detection and Skipping Using Deep Learning on the Internet of Drones

Ahmed, U., Lin, J. C., & Srivastava, G. (2021) · IEEE Internet of Things Magazine · doi:10.1109/iotm.001.2100088 · Cited by 5 · see citing works

Multi-aspect detection and classification with multi-feed dynamic frame skipping in vehicle of internet things

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SSP Framework: A New Approach to Designing Lightweight Convolutional Neural Networks

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Anomaly Detection in Red Reflex Images Using Deep Learning Approaches

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IoT based application designing of Deep Fake Test for Face animation

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Cloud Detection From High-Resolution Remote Sensing Images Based on Convolutional Neural Networks With Geographic Features and Contextual Information

Cao, Y., Sui, B., Zhang, S., & Qin, H. (2023) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2023.3251364 · Cited by 5 · see citing works

uvaNet: A Deep Learning Framework for Precise Detection of Potato Leaf Diseases in Sustainable Agricultural Production

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Enhanced Zero-Shot YOLOv10 for Multi-Class Tiny-Object Detection of Steel Surface Defects

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Evaluating the Performance of DenseNet in ECG Report Automation

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Noncontrast CT-based deep learning for predicting intracerebral hemorrhage expansion incorporating growth of intraventricular hemorrhage

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A multicenter deep learning framework integrating radiomics and vision transformers for comprehensive ovarian tumor analysis from ultrasound imaging

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Optimized Visual Recognition Through a Deep Convolutional Neural Network With Hierarchical Modular Organization

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Pneumonia Detection Using Deep Transfer Learning in Gender Specific Chest X-ray Images

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ML-Stealer: Stealing Prediction Functionality of Machine Learning Models with Mere Black-Box Access

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Deep Feature Detection Approach for COVID-19 Classification based on X-ray Images

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Building Usage Classification Using a Transformer-based Multimodal Deep Learning Method

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A novel framework for quantitative rhinoplasty evaluation by ResNet convolutional neural network

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A Multimodal AI Framework for Cross-Cultural Pragmatic Competence Analysis in Global English Communication

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2D-SNet: A Lightweight Network for Person Re-Identification on the Small Data Regime

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Deciphering pixel insights: A deep dive into deep learning strategies for enhanced indoor depth estimation

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Relation Explore Convolutional Block Attention Module for Skin Lesion Classification

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Breast Cancer Detection Using ResNet and DenseNet Architecture

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DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs

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Discussion on image recognition under different conditions of Resnet and Densenet

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ResDNet: Efficient Dense Multi-Scale Representations With Residual Learning for High-Level Vision Tasks

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Introducing attention shortcuts in convolutional neural networks

Erroz, D., & Galar, M. (2025) · Electronic Research Archive · doi:10.3934/era.2025215

Sparsely Connected Convolutional Networks.Preprint

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