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Image Classification

3781 papers with code • 168 benchmarks • 240 datasets

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

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Brain Storm Optimization Based Swarm Learning for Diabetic Retinopathy Image Classification

no code yet • 24 Apr 2024

Federated learning, as a privacy-preserving machine learning architecture, has shown promising performance in balancing data privacy and model utility by keeping private data on the client's side and using a central server to coordinate a set of clients for model training through aggregating their uploaded model parameters.

 
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A review of deep learning-based information fusion techniques for multimodal medical image classification

no code yet • 23 Apr 2024

Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it combines information from various imaging modalities to provide a more comprehensive understanding of the underlying pathology.

 
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An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models

no code yet • 23 Apr 2024

In traditional statistical learning, data points are usually assumed to be independently and identically distributed (i. i. d.)

 
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Deep multi-prototype capsule networks

no code yet • 23 Apr 2024

Capsule networks are a type of neural network that identify image parts and form the instantiation parameters of a whole hierarchically.

 
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CKD: Contrastive Knowledge Distillation from A Sample-wise Perspective

no code yet • 22 Apr 2024

Note that constraints on intra-sample similarities and inter-sample dissimilarities can be efficiently and effectively reformulated into a contrastive learning framework with newly designed positive and negative pairs.

 
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WangLab at MEDIQA-M3G 2024: Multimodal Medical Answer Generation using Large Language Models

no code yet • 22 Apr 2024

This paper outlines our submission to the MEDIQA2024 Multilingual and Multimodal Medical Answer Generation (M3G) shared task.

 
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EncodeNet: A Framework for Boosting DNN Accuracy with Entropy-driven Generalized Converting Autoencoder

no code yet • 21 Apr 2024

Our experimental results demonstrate that EncodeNet improves the accuracy of VGG16 from 92. 64% to 94. 05% on CIFAR-10 and RestNet20 from 74. 56% to 76. 04% on CIFAR-100.

 
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I2CANSAY:Inter-Class Analogical Augmentation and Intra-Class Significance Analysis for Non-Exemplar Online Task-Free Continual Learning

no code yet • 21 Apr 2024

Online task-free continual learning (OTFCL) is a more challenging variant of continual learning which emphasizes the gradual shift of task boundaries and learns in an online mode.

 
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Nested-TNT: Hierarchical Vision Transformers with Multi-Scale Feature Processing

no code yet • 20 Apr 2024

ViT divides an image into several local patches, known as "visual sentences".

 
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Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment

no code yet • 19 Apr 2024

This study proposes a multi-modal fusion framework Multitrans based on the Transformer architecture and self-attention mechanism.

 
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