https://github.com/Hadisalman/robust-verify-benchmark
Towards Deep Learning Models Resistant to Adversarial Attacks
Papers with Code 아카이브
Sound Event Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 5
- 보존된 평가 기록
- 25
Sound Event Detection (SED) is the task of recognizing the sound events and their respective temporal start and end time in a recording. Sound events in real life do not always occur in isolation, but tend to considerably overlap with each other. Recognizing such overlapping sound events is referred as polyphonic SED.
Source: A report on sound event detection with different binaural features
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Jeffkang-94/pytorch-adversarial-attack
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/JiuSenso/SELD-TCN
SELD-TCN: Sound Event Localization & Detection via Temporal Convolutional Networks
https://github.com/KnowledgeDiscovery/FaceSec
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/Machine-Listeners-Valencia/seld-dcase2021
https://github.com/MiviaLab/DENet
https://github.com/P2333/Max-Mahalanobis-Training
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/SafiyaJan/Attacking-Neural-Networks
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/TonyYaoMSU/ProjectedGradientDescent
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/VishaalMK/VectorDefense
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/YinDFY/PGD_for_targeted_attack
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/Zoky-2020/Set-level_Guidance_Attack
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/abahram77/mnistChallenge
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/abahram77/mnist_challenge
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/albertmillan/adversarial-training-pytorch
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/amerch/CIFAR100-Training
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/andrewilyas/ens-adv-train-attack
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/anuragkr90/webly-labeled-sounds
https://github.com/arobey1/advbench
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/arobey1/mbrdl
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/benbogart/bird_vocalization_classification
Adaptive pooling operators for weakly labeled sound event detection
https://github.com/bethgelab/cifar10_challenge
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/bingcheng45/hnr-extension
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/boyellow/adaad
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/cchinchristopherj/Right-Whale-Unsupervised-Model
Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection
https://github.com/cdluminate/advrank
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/cdluminate/advrank-pub
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/cleverhans-lab/cleverhans
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/cs-giung/course-dl-TP
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/dacostaHugo/Adversarial_attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/ee17b031-iittp/Projected-Gradient-Descent-with-CIFAR10
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/eldadp100/Towards-Deep-Learning-Models-Resistant-to-Adversarial-Attacks-Implementation
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/eldadp100/cnn_course_final
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/eleGAN23/QGAN
PHNNs: Lightweight Neural Networks via Parameterized Hypercomplex Convolutions
https://github.com/eleGAN23/QVAE
PHNNs: Lightweight Neural Networks via Parameterized Hypercomplex Convolutions
https://github.com/giusenso/seld-tcn
SELD-TCN: Sound Event Localization & Detection via Temporal Convolutional Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.