Object Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.
<span style="color:grey; opacity: 0.6">( Image credit: Tensorflow Object Detection API )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/RaghavHub/rekuten_hack
https://github.com/RajdeepBiswas/Manufacturing-Quality-Inspection
https://github.com/RajuGudhe/Cancer_Tissue_Detection
https://github.com/RameshBattu/Convolutional-Neural-Network-on-CIFAR-10-DataSet
https://github.com/RangiLyu/mmdetection_test
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
https://github.com/Rizo-R/chess-cv
Chessboard and chess piece recognition with the support of neural networks
https://github.com/SANKHA1/Vehicle-Detection
https://github.com/SConsul/ReSeg
ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks
https://github.com/SSN15/Traffic-sign-recognition-using-deep-learning-and-computer-vision
https://github.com/SaeedShurrab/SimSiam-pytorch
A Simple Framework for Contrastive Learning of Visual Representations
https://github.com/Sakib1263/DenseNet-1D-2D-Tensorflow-Keras
https://github.com/Sakib1263/Inception-InceptionResNet-1D-2D-Tensorflow-Keras
https://github.com/Sakib1263/Inception-Model-Builder-Tensorflow-Keras
https://github.com/SamsungSAILMontreal/ForestDiffusion
https://github.com/SensorsINI/v2e_exps_public
https://github.com/SergioVillarruel/FruitDetector3D
Food Image Recognition by Using Convolutional Neural Networks (CNNs)
https://github.com/SforAiDl/CountCLIP
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/ShiyuLiang/odin-pytorch
https://github.com/ShreyasArthur/StyleGAN-2-with-Urban-Plans
https://github.com/Shritesh99/100DaysofMLCodeChallenge
https://github.com/ShubhayanS/Multiclass-Diabetic-Retinopathy-Detection
Transfer Learning based Detection of Diabetic Retinopathy from Small Dataset
https://github.com/SiavashCS/sgan_simple
https://github.com/SicongLiu/StreamingTopK
https://github.com/SimJeg/FC-DenseNet
https://github.com/SmartEngines/stoppers_modelling
https://github.com/Sooram/cnn
https://github.com/Sooram/stn
https://github.com/SpaceNetChallenge/utilities
https://github.com/Speacer/Super-Resolution-Generative-Adversarial-Networks
https://github.com/Stomper10/CheXpert
https://github.com/TetsumichiUmada/food_app
Food Image Recognition by Using Convolutional Neural Networks (CNNs)
https://github.com/TooTouch/WhiteBox-Part1
https://github.com/Tushar-N/interaction-hotspots
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.