https://github.com/AlanYangYi/PhotoStyleRecongnizer
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
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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.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
CP-decomposition with Tensor Power Method for Convolutional Neural Networks Compression
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Music Artist Classification with Convolutional Recurrent Neural Networks
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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
MDMLP: Image Classification from Scratch on Small Datasets with MLP
Learning Transferable Visual Models From Natural Language Supervision
Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.