Papers with Code 아카이브
Robotic Grasping
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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This task is composed of using Deep Learning to identify how best to grasp objects using robotic arms in different scenarios. This is a very complex task as it might involve dynamic environments and objects unknown to the network.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Nikhil9786/Implemetation-of-VGG16-ResNet18-InceptionV2-on-Cifar100
https://github.com/PaddlePaddle/PaddleClas
https://github.com/PerfectExamples/Perfect-TensorFlow-Demo-Vision
https://github.com/PratikTayshete/Cats-and-Dogs-Image-Classification
https://github.com/Puzer/stylegan-encoder
https://github.com/Radvian/apple-img
https://github.com/Radvian/apple_img
https://github.com/RemiArbache/style-transfer-M2
https://github.com/Robinatp/Tensorflow_Model_Inception
https://github.com/RudreshVeerkhare/StyleGan
https://github.com/Sakib1263/Inception-InceptionResNet-1D-2D-Tensorflow-Keras
https://github.com/Sakib1263/Inception-Model-Builder-Tensorflow-Keras
https://github.com/Schlam/inceptionv3-transfer-learning
https://github.com/SophiaYuSophiaYu/ImageCaption
https://github.com/SteveHao74/shahao_GR-ConvNet
Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network
https://github.com/Sunil4423/-cassava_disease_classification
https://github.com/ThanasisMattas/smartflow
https://github.com/TianheWu/LGPNet
https://github.com/UnofficialJuliaMirror/DeepMark-deepmark
https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark
https://github.com/Urmil28/Medical-Image-Analysis
https://github.com/YantianZha/Affordance-Aware-Imitation-Learning
Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping
https://github.com/adithyamurali/TaskGrasp
Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented Grasping
https://github.com/alisha17/benchmarks
https://github.com/allenai/robustnav
PyRobot: An Open-source Robotics Framework for Research and Benchmarking
https://github.com/anked10/CNNs_tensorflow2_InceptionV3-maderas
https://github.com/ashutosh1919/FaceGenerationStyleGAN
https://github.com/athulyashyju/sample-project
https://github.com/atspatel/pydata_inception_v2
https://github.com/augcog/dttd2
https://github.com/augcog/robust-digital-twin-tracking
https://github.com/axkoenig/reflex_stack
The Role of Tactile Sensing in Learning and Deploying Grasp Refinement Algorithms
https://github.com/ayushdabra/stanford-dogs-dataset-classification
https://github.com/ayushgupta9198/gan
https://github.com/ayushgupta9198/stylegan
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.