Automated Flower Classification over a Large Number of Classes

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Histograms of Oriented Gradients for Human Detection

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Learning with Kernels

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Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images

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Visual Atoms: Pre-Training Vision Transformers with Sinusoidal Waves

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Soft assignment of visual words as Linear Coordinate Coding and optimisation of its reconstruction error

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Transferable AutoML by Model Sharing Over Grouped Datasets

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Normalized Diversification

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A Benchmark and Baseline for Language-Driven Image Editing

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Transferability-Guided Cross-Domain Cross-Task Transfer Learning

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Friendly Sharpness-Aware Minimization

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Fusion that matters: convolutional fusion networks for visual recognition

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Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks

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Deep image synthesis from intuitive user input: A review and perspectives

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Text-to-image synthesis with self-supervised learning

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Flower Recognition System with Optimized Features for Deep Features

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Epidermal piezoresistive structure with deep learning-assisted data translation

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Helpful or Harmful: Inter-task Association in Continual Learning

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Semantics-Guided Intra-Category Knowledge Transfer for Generalized Zero-Shot Learning

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Salient Mask-Guided Vision Transformer for Fine-Grained Classification

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LFR-GAN: Local Feature Refinement based Generative Adversarial Network for Text-to-Image Generation

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Concept-Guided Prompt Learning for Generalization in Vision-Language Models

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Sparse representations based attribute learning for flower classification

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Decoupled Learning for Conditional Adversarial Networks

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MMFL: Multimodal Fusion Learning for Text-Guided Image Inpainting

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Frustratingly Easy Transferability EstimationPreprint

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Context-Aware Robust Fine-Tuning

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Large Language Models are Good Prompt Learners for Low-Shot Image Classification

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Efficient segmentation of leaves in semi-controlled conditions

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Toward Good Practices for Fine-Grained Maize Cultivar Identification With Filter-Specific Convolutional Activations

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Multi-channel multi-model feature learning for face recognition

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Preliminary study on angiosperm genus classification by weight decay and combination of most abundant color index with fractional Fourier entropy

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Self-Paced Adversarial Training for Multimodal Few-Shot Learning

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Boosting Standard Classification Architectures Through a Ranking Regularizer

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Generalized Zero-Shot Learning Via Multi-Modal Aggregated Posterior Aligning Neural Network

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CRD-CGAN: category-consistent and relativistic constraints for diverse text-to-image generation

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AIFS-DATASET for Few-Shot Aerial Image Scene Classification

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Bias-Eliminated Semantic Refinement for Any-Shot Learning

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Smart App Attack: Hacking Deep Learning Models in Android Apps

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Composition-Aware Image Steganography Through Adversarial Self-Generated Supervision

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GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning

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

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Multi-Modality Deep Network for Extreme Learned Image Compression

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Recent Advances in Text-to-Image Synthesis: Approaches, Datasets and Future Research Prospects

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Learning Expressive Prompting With Residuals for Vision Transformers

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APoLLo : Unified Adapter and Prompt Learning for Vision Language Models

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Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods

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EfficientTrain++: Generalized Curriculum Learning for Efficient Visual Backbone Training

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Language Models as Black-Box Optimizers for Vision-Language Models

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VeCLIP: Improving CLIP Training via Visual-Enriched Captions

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LR-CNN for fine-grained classification with varying resolution

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Generating Images From Spoken Descriptions

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ConvMLP: Hierarchical Convolutional MLPs for VisionPreprint

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Why Do Better Loss Functions Lead to Less Transferable Features?Preprint

Kornblith, S., Chen, T., Lee, H., & Norouzi, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.16402 · Cited by 35

ePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill Identification

Usuyama, N., Delgado, N. L., Hall, A. K., & Lundin, J. (2020) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00463 · Cited by 22

Incremental Residual Concept Bottleneck Models

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Low-Rank Rescaled Vision Transformer Fine-Tuning: A Residual Design Approach

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How could a subcellular image, or a painting by Van Gogh, be similar to a great white shark or to a pizza?

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Multiview Semantic Representation for Visual Recognition

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AI Gauge: Runtime Estimation for Deep Learning in the Cloud

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AI Illustrator: Art Illustration Generation Based on Generative Adversarial Network

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Modality Disentangled Discriminator for Text-to-Image Synthesis

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Edge Guided Progressively Generative Image Outpainting

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Metric learning for image-based flower cultivars identification

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Interpretability-Guided Defense Against Backdoor Attacks to Deep Neural Networks

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A large-scale hyperspectral dataset for flower classification

Zheng, Y., Zhang, T., & Fu, Y. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107647 · Cited by 22

Image forgery detection using Deep Neural Network

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Cross-Domain Few-Shot Classification based on Lightweight Res2Net and Flexible GNN

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Text-to-Face Generation with StyleGAN2

Ayanthi, D. M. A., & Munasinghe, S. (2022) · doi:10.5121/csit.2022.120805 · Cited by 23

PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks

Ding, N., Chen, X., Levinboim, T., Changpinyo, S., & Soricut, R. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19830-4_15 · Cited by 27

Improving fine-tuning of self-supervised models with Contrastive Initialization

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GuidedMixup: An Efficient Mixup Strategy Guided by Saliency Maps

Kang, M., & Kim, S. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i1.25191 · Cited by 24

The Accelerated Inference of a Novel Optimized YOLOv5-LITE on Low-Power Devices for Railway Track Damage Detection

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The Euclidean Space is Evil: Hyperbolic Attribute Editing for Few-shot Image Generation

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SODA: Bottleneck Diffusion Models for Representation Learning

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MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric

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Category co-occurrence modeling for large scale scene recognition

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Supervised and unsupervised learning in animal classification

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Automatic recognition of flower species in the natural environment

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A Novel Method for Traffic Sign Recognition Based on DCGAN and MLP With PILAE Algorithm

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What and Where: Learn to Plug Adapters via NAS for Multidomain Learning

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A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species Classification

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Semantic Rule Based Image Visual Feature Ontology Creation

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Flower Categorization using Deep Convolutional Neural NetworksPreprint

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A linearized framework and a new benchmark for model selection for fine-tuningPreprint

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Image dataset on the Chinese medicinal blossoms for classification through convolutional neural network

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Identification of medicinal plant using hybrid transfer learning technique

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Learning Sample Specific Weights for Late Fusion

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A comparative study of fine-grained classification methods in the context of the LifeCLEF plant identification challenge 2015

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Evolving Convolutional Neural Network and Its Application in Fine-Grained Visual Categorization

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Research progress of zero-shot learning beyond computer vision

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Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-Grained Visual Categorization

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Reusing Deep Neural Network Models through Model Re-engineering

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ProbVLM: Probabilistic Adapter for Frozen Vison-Language Models

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LoGoPrompt: Synthetic Text Images Can Be Good Visual Prompts for Vision-Language Models

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