A survey on deep learning-based fine-grained object classification and semantic segmentation

ImageNet classification with deep convolutional neural networks

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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ImageNet: A large-scale hierarchical image database

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Going deeper with convolutions

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Fully convolutional networks for semantic segmentation

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Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

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DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

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Advances in Neural Information Processing Systems 25

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Backpropagation Applied to Handwritten Zip Code Recognition

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Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

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Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

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On the Properties of Neural Machine Translation: Encoder–Decoder Approaches

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Selective Search for Object Recognition

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Spatial transformer networks

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CNN Features Off-the-Shelf: An Astounding Baseline for Recognition

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Learning Deconvolution Network for Semantic Segmentation

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Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

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DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

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Recurrent Models of Visual AttentionPreprint

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Recurrent Neural Network RegularizationPreprint

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Long short-term memory recurrent neural network architectures for large scale acoustic modeling

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Mutual-information-based registration of medical images: a survey

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Edge Boxes: Locating Object Proposals from Edges

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Learning Hierarchical Features for Scene Labeling

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Describing Textures in the Wild

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Bilinear CNN Models for Fine-Grained Visual Recognition

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A Novel Connectionist System for Unconstrained Handwriting Recognition

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Advances in Neural Information Processing Systems 5

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Learning Rich Features from RGB-D Images for Object Detection and Segmentation

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Going Deeper with Convolutions

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Part-Based R-CNNs for Fine-Grained Category Detection

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Simultaneous Detection and Segmentation

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Multiscale Combinatorial Grouping

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BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation

Dai, J., He, K., & Sun, J. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.191 · Cited by 1,118 · see citing works

On the Properties of Neural Machine Translation: Encoder-Decoder ApproachesPreprint

Cho, K., van Merriënboer, B., Bahdanau, D., et al. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1409.1259 · Cited by 1,112 · see citing works

Multiple Object Recognition with Visual Attention

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The application of two-level attention models in deep convolutional neural network for fine-grained image classification

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CNN Features off-the-shelf: an Astounding Baseline for Recognition

Razavian, A. S., Azizpour, H., Sullivan, J., & Carlsson, S. (2014) · arXiv · doi:10.48550/arxiv.1403.6382 · Cited by 607 · see citing works

Bird Species Categorization Using Pose Normalized Deep Convolutional NetsPreprint

Branson, S., Horn, G. V., Belongie, S., & Perona, P. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1406.2952 · Cited by 600 · see citing works

Action Recognition using Visual AttentionPreprint

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Part-Stacked CNN for Fine-Grained Visual Categorization

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Diversified Visual Attention Networks for Fine-Grained Object Classification

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POOF: Part-Based One-vs.-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation

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Minimal gated unit for recurrent neural networks

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Deep LAC: Deep localization, alignment and classification for fine-grained recognition

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Multiple Granularity Descriptors for Fine-Grained Categorization

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Dog Breed Classification Using Part Localization

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BiCoS: A Bi-level co-segmentation method for image classification

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Fine-Grained Categorization by Alignments

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BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic SegmentationPreprint

Dai, J., He, K., & Sun, J. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1503.01640 · Cited by 146 · see citing works

Unsupervised Template Learning for Fine-Grained Object Recognition

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Image Classification and Retrieval are ONE

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Multi-Digit Recognition Using a Space Displacement Neural Network

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Attention for Fine-Grained CategorizationPreprint

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Fully Convolutional Attention Localization Networks: Efficient Attention Localization for Fine-Grained RecognitionPreprint

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Fine-grained classification via mixture of deep convolutional neural networks

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Subset feature learning for fine-grained category classification

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Learning fine-grained features via a CNN Tree for Large-scale Classification

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InterActive: Inter-Layer Activeness Propagation

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Efficient Large-Scale Structured Learning

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Feature selection and feature learning for high-dimensional batch reinforcement learning: A survey

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Part Localization using Multi-Proposal Consensus for Fine-Grained Categorization

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InterActive: Inter-Layer Activeness PropagationPreprint

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Learning Fine-grained Features via a CNN Tree for Large-scale ClassificationPreprint

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Fine-Grained Classification via Mixture of Deep Convolutional Neural NetworksPreprint

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Federated Learning in Mobile Edge Networks: A Comprehensive Survey

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Attention gated networks: learning to leverage salient regions in medical images

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A Survey of Deep Learning-Based Object Detection

Jiao, L., Zhang, F., Liu, F., Yang, S., Li, L., Feng, Z., & Qu, R. (2019) · IEEE Access · doi:10.1109/access.2019.2939201 · Cited by 1,392 · see citing works

Convolutional neural network: a review of models, methodologies and applications to object detection

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Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images

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BBN: Bilateral-Branch Network With Cumulative Learning for Long-Tailed Visual Recognition

Zhou, B., Cui, Q., Wei, X.-S., & Chen, Z.-M. (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/cvpr42600.2020.00974 · Cited by 949 · see citing works

A Brief Survey on Semantic Segmentation with Deep Learning

Hao, S., Zhou, Y., & Guo, Y. (2020) · Neurocomputing · doi:10.1016/j.neucom.2019.11.118 · Cited by 608 · see citing works

Fine-Grained Image Analysis With Deep Learning: A Survey

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Understanding Deep Learning Techniques for Image Segmentation

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Object-Part Attention Model for Fine-Grained Image Classification

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Electronic Nose and Its Applications: A Survey

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A Survey on Theories and Applications for Self-Driving Cars Based on Deep Learning Methods

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Deep Learning and Transformer Approaches for UAV-Based Wildfire Detection and Segmentation

Ghali, R., Akhloufi, M. A., & Mseddi, W. S. (2022) · Sensors · doi:10.3390/s22051977 · Cited by 176 · see citing works

A review on lung boundary detection in chest X-rays

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ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images

Liu, Y., Shen, J., Yang, L., Bian, G., & Yu, H. (2022) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2022.104087 · Cited by 160 · see citing works

A survey of semi- and weakly supervised semantic segmentation of images

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Deep Learning for Retail Product Recognition: Challenges and Techniques

Wei, Y.-C., Tran, S. N., Xu, S., Kang, B. H., & Springer, M. (2020) · Computational Intelligence and Neuroscience · doi:10.1155/2020/8875910 · Cited by 141 · see citing works

An Overview of Contour Detection Approaches

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A Survey of Video Surveillance Systems in Smart City

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Forest fire surveillance systems: A review of deep learning methods

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Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning

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Semantics for Robotic Mapping, Perception and Interaction: A Survey

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Visual SLAM Integration With Semantic Segmentation and Deep Learning: A Review

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A Vision-Based Pipeline for Vehicle Counting, Speed Estimation, and Classification

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Object Detection with Transformers: A Review

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BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared Videos

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Single-View 3D reconstruction: A Survey of deep learning methods

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Surgical tool segmentation using a hybrid deep CNN-RNN auto encoder-decoder

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Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification

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Bird Image Retrieval and Recognition Using a Deep Learning Platform

Huang, Y., & Basanta, H. (2019) · IEEE Access · doi:10.1109/access.2019.2918274 · Cited by 78 · see citing works

Potential Bands of Sentinel-2A Satellite for Classification Problems in Precision Agriculture

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Action Recognition With Spatial-Temporal Discriminative Filter Banks

Martínez, B., Modolo, D., Xiong, Y., & Tighe, J. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00558 · Cited by 75 · see citing works

Deep Learning for Fine-Grained Image Analysis: A SurveyPreprint

Wei, X.-S., Wu, J., & Cui, Q. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.03069 · Cited by 89 · see citing works

Biometric identification of sheep via a machine-vision system

Hitelman, A., Edan, Y., Godo, A., Berenstein, R., Lepar, J., & Halachmi, I. (2022) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2022.106713 · Cited by 76 · see citing works

Improving the Performance of Deep Neural Networks Using Two Proposed Activation Functions

Alkhouly, A. A., Mohammed, A., & Hefny, H. A. (2021) · IEEE Access · doi:10.1109/access.2021.3085855 · Cited by 75 · see citing works

3D image recognition using new set of fractional-order Legendre moments and deep neural networks

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An Automatic Deep Segmentation Network for Pixel-Level Welding Defect Detection

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A review of distributed solar forecasting with remote sensing and deep learning

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A Survey of Scene Understanding by Event Reasoning in Autonomous Driving

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Pointview-GCN: 3D Shape Classification With Multi-View Point Clouds

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Gated Recurrent Multiattention Network for VHR Remote Sensing Image Classification

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A Comprehensive Review of Group Activity Recognition in Videos

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Diagnostic Accuracy of Artificial Intelligence in Glaucoma Screening and Clinical Practice

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Deep Listwise Triplet Hashing for Fine-Grained Image Retrieval

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Detection of unwanted traffic congestion based on existing surveillance system using in freeway via a CNN-architecture trafficnet

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A Triple-Stream Network With Cross-Stage Feature Fusion for High-Resolution Image Change Detection

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Towards Automated Ship Detection and Category Recognition from High-Resolution Aerial Images

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Adaptive Mutual Learning for Unsupervised Domain Adaptation

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Ship Classification in SAR Images With Geometric Transfer Metric Learning

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Physiognomy: Personality traits prediction by learning

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Semi-supervised Ladder Networks for Speech Emotion Recognition

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Distribution Shift Metric Learning for Fine-Grained Ship Classification in SAR Images

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Addressing significant challenges for animal detection in camera trap images: a novel deep learning-based approach

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Focal Dice Loss-Based V-Net for Liver Segments Classification

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Knowing Your Dog Breed: Identifying a Dog Breed with Deep Learning

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Deep LF-Net: Semantic lung segmentation from Indian chest radiographs including severely unhealthy images

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Machine learning models based on hyperspectral imaging for pre-harvest tomato fruit quality monitoring

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Deep Learning in Cybersecurity

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Dates Fruit Recognition: From Classical Fusion to Deep Learning

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Visually interpretable deep network for diagnosis of breast masses on mammograms

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Detecting helicobacter pylori in whole slide images via weakly supervised multi-task learning

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Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features

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Mapping Key Indicators of Forest Restoration in the Amazon Using a Low-Cost Drone and Artificial Intelligence

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A survey on deep learning-based precise boundary recovery of semantic segmentation for images and point clouds

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New deep learning method for efficient extraction of small water from remote sensing images

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Medical Ultrasound Image Quality Assessment for Autonomous Robotic Screening

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Learning Multi-Subset of Classes for Fine-Grained Food Recognition

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Portrait Segmentation Using Ensemble of Heterogeneous Deep-Learning Models

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MEP-3M: A large-scale multi-modal E-commerce product dataset

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A Robust Face Recognition Method Combining LBP with Multi-mirror Symmetry for Images with Various Face Interferences

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Deep reinforcement learning in edge networks: Challenges and future directions

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SILIC: A cross database framework for automatically extracting robust biodiversity information from soundscape recordings based on object detection and a tiny training dataset

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GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

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Few-shot fine-grained fish species classification via sandwich attention CovaMNet

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An improved GrabCut on multiscale features

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Computing Valid P-Values for Image Segmentation by Selective Inference

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Towards Multi-source Adaptive Semantic Segmentation

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A Risk-Aware Architecture for Autonomous Vehicle Operation Under Uncertainty

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A Comprehensive Review of Land Use and Land Cover Change Based on Knowledge Graph and Bibliometric Analyses

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Deep Saliency With Channel-Wise Hierarchical Feature Responses for Traffic Sign Detection

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Improving classification with semi-supervised and fine-grained learning

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Using Deep Learning to Identify Potential Roof Spaces for Solar Panels

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Online Learning of Finite and Infinite Gamma Mixture Models for COVID-19 Detection in Medical Images

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A Survey of Fine-Grained Image Classification Based on Deep Learning

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Deep Learning for Fine-Grained Image Analysis: A SurveyPreprint

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Fine-Grained Image Analysis With Deep Learning: A Survey

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Fine-grained image classification using deep learning

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