https://github.com/Elman295/Vision-Mamba-MNIST-
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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.
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Reversible Architectures for Arbitrarily Deep Residual Neural Networks
Beyond Cats and Dogs: Semi-supervised Classification of fuzzy labels with overclustering
Very Deep Convolutional Networks for Large-Scale Image Recognition
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
Learning Spatial Regularization with Image-level Supervisions for Multi-label Image Classification
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Learning Efficient Convolutional Networks through Network Slimming
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Very Deep Convolutional Networks for Large-Scale Image Recognition
Momentum Contrast for Unsupervised Visual Representation Learning
SRM : A Style-based Recalibration Module for Convolutional Neural Networks
Very Deep Convolutional Networks for Large-Scale Image Recognition
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Pre-training Music Classification Models via Music Source Separation
Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning:A Systematic Study
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.