https://github.com/houchengbin/fossil-id-multiview-deep-ensembles
공식 코드Fossil Image Identification using Deep Learning Ensembles of Data Augmented Multiviews
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/houchengbin/fossil-image-identification
공식 코드Fossil Image Identification using Deep Learning Ensembles of Data Augmented Multiviews
https://github.com/howardyclo/clcc-cvpr21
공식 코드https://github.com/hqjenny/CoDeNet
공식 코드CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs
https://github.com/hrayrhar/limit-label-memorization
공식 코드Improving Generalization by Controlling Label-Noise Information in Neural Network Weights
https://github.com/hrzhang1123/dtfd-mil
공식 코드https://github.com/hseung88/adaact
공식 코드An Adaptive Method Stabilizing Activations for Enhanced Generalization
https://github.com/hsilva664/discrete_nn
공식 코드What to Do When Your Discrete Optimization Is the Size of a Neural Network?
https://github.com/hszhao/PSPNet
공식 코드https://github.com/htqin/awesome-model-quantization
공식 코드https://github.com/htqin/dsg
공식 코드Diverse Sample Generation: Pushing the Limit of Generative Data-free Quantization
https://github.com/huangleiBuaa/ONI
공식 코드https://github.com/huangleiBuaa/OthogonalWN
공식 코드https://github.com/huangmozhilv/u2net_torch
공식 코드3D U$^2$-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation
https://github.com/huangzizheng01/shufflemamba
공식 코드Stochastic Layer-Wise Shuffle: A Good Practice to Improve Vision Mamba Training
https://github.com/huanranchen/ASRNorm
공식 코드AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework
https://github.com/huanranchen/AdversarialAttacks
공식 코드Rethinking Model Ensemble in Transfer-based Adversarial Attacks
https://github.com/huanzhang12/Adversarial_Survey
공식 코드https://github.com/huanzhang12/ZOO-Attack
공식 코드https://github.com/huawei-noah/CV-Backbones/tree/master/tnt_pytorch
공식 코드https://github.com/huawei-noah/CV-backbones
공식 코드Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/huawei-noah/Efficient-Computing
공식 코드GPT4Image: Can Large Pre-trained Models Help Vision Models on Perception Tasks?
https://github.com/huawei-noah/efficient-ai-backbones
공식 코드https://github.com/huawei-noah/ghostnet
공식 코드https://github.com/huawei-noah/ghostnet/tree/master/tinynet_pytorch
공식 코드Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/huawei-noah/noah-research
공식 코드Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection
https://github.com/huaxiuyao/ARML
공식 코드https://github.com/huaxiuyao/DMVST-Net
공식 코드Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
https://github.com/huaxiuyao/HSML
공식 코드https://github.com/huaxiuyao/mlti
공식 코드https://github.com/huggingface/autotrain-advanced
공식 코드https://github.com/huggingface/datasets
공식 코드Datasets: A Community Library for Natural Language Processing
https://github.com/huggingface/pytorch-image-models
공식 코드https://github.com/hugo-oliveira/fsws_metalearning
공식 코드Meta-Learners for Few-Shot Weakly-Supervised Medical Image Segmentation
https://github.com/hugo0076/halo
공식 코드HALO: Robust Out-of-Distribution Detection via Joint Optimisation
https://github.com/huhengtong/one-bit-supervision
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.