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SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathology
Multiple Instance Learning on Pathology Slides
Mixup Data augmentation with TensorFlow 2 with intergration in tf.data - Full Stack Deep Learning.
Normality Guided Multiple Instance Learning for Weakly Supervised Video Anomaly Detection
Prompt-MIL: Boosting Multi-Instance Learning Schemes via Task-specific Prompt Tuning
Mixup augmentation for generalizable speech separation - Ashish Alex
What is Mixup Augmentation
[S+SSPR 2020] On Calibration of Mixup Training for Deep Neural Networks
ICPR2022 || Bone Age Estimation with Multiple Instance Learning
Dropout, augmentation, Mixup and label smoothing | Deep Learning, Lecture 10B
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Last Updated: September 28, 2026
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This is a short teaser talk of the paper " Presenter: Christopher Hendra Date & Time: 28 July 2021, 9am-5pm Abstract: In recent years, there has been a surge in the ... Are you having trouble with your accent? Do you find it hard to understand people from other countries? If so, you may be ... Authors: Dinkar Juyal; Siddhant Shingi; Syed Ashar Javed; Harshith Padigela; Chintan Shah; Anand Sampat; Archit Khosla; John ... When it comes to applying computer vision in the medical field, most tasks involve either 1) image classification for diagnosis or 2) ... Authors: Park, Seongheon*; Kim, Hanjae; Kim, Minsu; Kim, Dahye; Sohn , Kwanghoon Description: Weakly supervised Video ... 2021 Intelligent Sensing Winter School Authors: Juan Maroñas, Daniel Ramos and Roberto Paredes Abstract: Deep Neural Networks (DNN) represent the state of the art ... This video is about our paper published at the 26th International Conference on Pattern Recognition, 2022. Random crops and flips raise a CIFAR-10 model's test accuracy from 43.0% to 54.6%. The video covers where else a regularizer ...
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