Papers with Code 아카이브
Image Classification
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/emanuelevivoli/awesome-comics-understanding
공식 코드One missing piece in Vision and Language: A Survey on Comics Understanding
https://github.com/emasa/balpoe-calibratedlt
공식 코드Balanced Product of Calibrated Experts for Long-Tailed Recognition
https://github.com/embeddedml-edagroup/pit
공식 코드Lightweight Neural Architecture Search for Temporal Convolutional Networks at the Edge
https://github.com/emi-group/mixer-snn
공식 코드Efficient Deep Spiking Multi-Layer Perceptrons with Multiplication-Free Inference
https://github.com/emprime/dcic
공식 코드https://github.com/emu1729/gist
공식 코드GIST: Generating Image-Specific Text for Fine-grained Object Classification
https://github.com/engrjavediqbal/wan
공식 코드Weakly Supervised Domain Adaptation for Built-up Region Segmentation in Aerial and Satellite Imagery
https://github.com/ennisthemennis/sparse-combo-net
공식 코드RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks
https://github.com/ensta-u2is/ldu
공식 코드https://github.com/epfml/attention-cnn
공식 코드On the Relationship between Self-Attention and Convolutional Layers
https://github.com/eric-ai-lab/pevit
공식 코드Parameter-efficient Model Adaptation for Vision Transformers
https://github.com/erichson/LipschitzRNN
공식 코드https://github.com/ericjang/odin
공식 코드WAIC, but Why? Generative Ensembles for Robust Anomaly Detection
https://github.com/ericotjo001/explainable_ai
공식 코드Improving Deep Neural Network Classification Confidence using Heatmap-based eXplainable AI
https://github.com/ericpts/reto
공식 코드Semi-supervised novelty detection using ensembles with regularized disagreement
https://github.com/erikberter/PolarFFA
공식 코드On the Improvement of Generalization and Stability of Forward-Only Learning via Neural Polarization
https://github.com/erikenglesson/gjs
공식 코드Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
https://github.com/erjui/DHO
공식 코드https://github.com/ermongroup/NDA
공식 코드https://github.com/eslambakr/emca
공식 코드https://github.com/essunny310/freestylenet
공식 코드https://github.com/eternal-vanguard/SpectralNET
공식 코드SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image Classification
https://github.com/ethan-y-lin/beyond_accuracy
공식 코드Beyond Accuracy: Metrics that Uncover What Makes a 'Good' Visual Descriptor
https://github.com/eugenechoi2004/cos429_final
공식 코드An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit Classification
https://github.com/eugenium/DGL
공식 코드https://github.com/eugenium/layerCNN
공식 코드https://github.com/euphoria16/tl-align
공식 코드https://github.com/euranova/calibrate_to_interpret
공식 코드https://github.com/evihuijben/ood_detection_mri
공식 코드https://github.com/excitedkid/vipaug
공식 코드https://github.com/explainableml/concept_realignment
공식 코드Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models
https://github.com/explainableml/datadream
공식 코드https://github.com/explainableml/imagefreezsl
공식 코드Image-free Classifier Injection for Zero-Shot Classification
https://github.com/eyalmichaeli/saspa-aug
공식 코드Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation
https://github.com/ezzzli/prompt-pate
공식 코드Exploring the Benefits of Visual Prompting in Differential Privacy
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.