https://github.com/pranit570/salientobjectsdetection
Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car
Papers with Code 아카이브
Self-Driving Cars
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Self-driving cars : the task of making a car that can drive itself without human guidance.
<span style="color:grey; opacity: 0.6">( Image credit: Learning a Driving Simulator )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pratibhaareddy/selfdrivingcar
https://github.com/preetam1997/Self-Driven-Car
https://github.com/rafa2000/Top-TensorFlow
https://github.com/rahul263-stack/Self-Driving-Car
https://github.com/rajathik/ObjectDetection
https://github.com/realcrane/BASAR-Black-box-Attack-on-Skeletal-Action-Recognition
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
https://github.com/realcrane/Defending-Black-box-Skeleton-based-Human-Activity-Classifiers
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
https://github.com/realcrane/SMART
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
https://github.com/realcrane/robustactionrecogniser
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
https://github.com/rehamessameltagoury/Urban-Self-Driving-Car
https://github.com/remic-othr/openmibood
Scaling Out-of-Distribution Detection for Real-World Settings
https://github.com/rohanchandra30/TrackNPred
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
https://github.com/romi514/TLSGAN
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
https://github.com/saumya0303/Attack_on_Image_Classification_Network
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
https://github.com/saumya0303/attack_image
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
https://github.com/saumya0303/image-classification-network-attack
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
https://github.com/sejong-rcv/2021.Paper.TransDSSL
https://github.com/sem6-nu/AI-PROJECT
https://github.com/sen-uni-kn/specrepair
SpecRepair: Counter-Example Guided Safety Repair of Deep Neural Networks
https://github.com/shoaibahmed/TSViz-Core
TSViz: Demystification of Deep Learning Models for Time-Series Analysis
https://github.com/shreyaspj20/Autonomous-Driving-Car-simulation-using-Pytorch
https://github.com/shunchan0677/deepware
https://github.com/simsal0r/mixture-of-decision-trees
MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning
https://github.com/snbhanja/SelfDrivingCarND_Term1_Project4_Behavioral_cloning
https://github.com/snehitvaddi/SelfDriving-Car_Deep-Learning
https://github.com/talk2car/Talk2Car
https://github.com/thanhtrung98/Pose_estimation
https://github.com/thanhtrung98/human_pose_estimation
https://github.com/theia-4869/semantic-poss-api
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
https://github.com/theneuralbeing/behavioral-cloning
https://github.com/theshuv/Autonomous-vehicle-steering-angle-prediction
https://github.com/thouyang/self_driving_with_corner_cases
https://github.com/tmoer/a0c
https://github.com/trungmanhhuynh/Object-Detection-Localization
MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation
https://github.com/uditsharma29/flynet-cann
A Hybrid Compact Neural Architecture for Visual Place Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.