Computer Vision
 
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Image Classification

3784 papers with code • 142 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

Libraries

Use these libraries to find Image Classification models and implementations

Datasets

Subtasks

CoProNN: Concept-based Prototypical Nearest Neighbors for Explaining Vision Models

teodorchiaburu/beexplainable • • 23 Apr 2024

A promising approach towards designing useful task specific explanations with domain experts is based on compositionality of semantic concepts.

12
23 Apr 2024
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Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image Classification

mahmad00/disjoint-sampling-for-hyperspectral-image-classification • 23 Apr 2024

This paper presents an innovative disjoint sampling approach for training SOTA models on Hyperspectral image classification (HSIC) tasks.

0
23 Apr 2024
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Pyramid Hierarchical Transformer for Hyperspectral Image Classification

mahmad00/pyformer • 23 Apr 2024

The traditional Transformer model encounters challenges with variable-length input sequences, particularly in Hyperspectral Image Classification (HSIC), leading to efficiency and scalability concerns.

0
23 Apr 2024
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Traditional to Transformers: A Survey on Current Trends and Future Prospects for Hyperspectral Image Classification

mahmad00/conventional-to-transformer-for-hyperspectral-image-classification-survey-2024 • 23 Apr 2024

Hyperspectral image classification is a challenging task due to the high dimensionality and complex nature of hyperspectral data.

0
23 Apr 2024
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3D-Convolution Guided Spectral-Spatial Transformer for Hyperspectral Image Classification

shyamvarahagiri/3d-convsst • • 20 Apr 2024

Furthermore, to have high classification performance, there should be a strong interaction between the HSI token and the class (CLS) token.

0
20 Apr 2024
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Next Generation Loss Function for Image Classification

zki-ph-imageanalysis/next-generation-loss • 19 Apr 2024

The 5 best functions found were evaluated for different model architectures on a set of standard datasets ranging from 2 to 102 classes and very different sizes.

3
19 Apr 2024
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Observation, Analysis, and Solution: Exploring Strong Lightweight Vision Transformers via Masked Image Modeling Pre-Training

wangsr126/mae-lite • • 18 Apr 2024

In this paper, we question if the extremely simple ViTs' fine-tuning performance with a small-scale architecture can also benefit from this pre-training paradigm, which is considerably less studied yet in contrast to the well-established lightweight architecture design methodology with sophisticated components introduced.

98
18 Apr 2024
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InfoMatch: Entropy Neural Estimation for Semi-Supervised Image Classification

kunzhan/infomatch • • 17 Apr 2024

Semi-supervised image classification, leveraging pseudo supervision and consistency regularization, has demonstrated remarkable success.

19
17 Apr 2024
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Vocabulary-free Image Classification and Semantic Segmentation

altndrr/vicss • • 16 Apr 2024

To address VIC, we propose Category Search from External Databases (CaSED), a training-free method that leverages a pre-trained vision-language model and an external database.

3
16 Apr 2024
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A variable metric proximal stochastic gradient method: an application to classification problems

koblererich/lisavm • • EURO Journal on Computational Optimization 2024

To control the variance of the objective's gradients, we use an automatic sample size selection along with a variable metric to precondition the stochastic gradient directions.

0
15 Apr 2024
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