Chapter 9.pdf
3.8 MB
Deformable MR Prostate
Segmentation via Deep
Feature Learning and Sparse
Patch Matching #Chapter9 @Machine_learn
Segmentation via Deep
Feature Learning and Sparse
Patch Matching #Chapter9 @Machine_learn
Chapter 11.pdf
3.1 MB
Scalable High
Performance Image
Registration Framework
by Unsupervised Deep
Feature Representations
Learning #Chapter11 @Machine_learn
Performance Image
Registration Framework
by Unsupervised Deep
Feature Representations
Learning #Chapter11 @Machine_learn
B978-0-12-810408-8.00013-4.pdf
1.2 MB
Characterization of Errors in Deep Learning-Based Brain MRI Segmentation #Chapter10 @Machine_learn
B978-0-12-810408-8.00019-5.pdf
1.8 MB
Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1 #Chapter14 @Machine_learn
Weighted Deep Neural Network Ensemble Approach for.pdf
1.4 MB
Weighted Deep Neural Network Ensemble Approach for
Multi-Domain Sentiment Analysis Author: @Raminmousa Doi:https://dx.doi.org/10.22105/jarie.2021.288364.1332 cite: Mousa, Ramin, et al. "Weighted Deep Neural Network Ensemble Approach for Multi-Domain Sentiment Analysis." Journal of Applied Research on Industrial Engineering (2021). link: https://www.researchgate.net/publication/360645256_Weighted_Deep_Neural_Network_Ensemble_Approach_for_Multi-Domain_Sentiment_Analysis @Machine_learn
Multi-Domain Sentiment Analysis Author: @Raminmousa Doi:https://dx.doi.org/10.22105/jarie.2021.288364.1332 cite: Mousa, Ramin, et al. "Weighted Deep Neural Network Ensemble Approach for Multi-Domain Sentiment Analysis." Journal of Applied Research on Industrial Engineering (2021). link: https://www.researchgate.net/publication/360645256_Weighted_Deep_Neural_Network_Ensemble_Approach_for_Multi-Domain_Sentiment_Analysis @Machine_learn
ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer
Github: https://github.com/locuslab/convmixer
Paper: https://arxiv.org/pdf/2201.09792v1.pdf
@Machine_learn
Github: https://github.com/locuslab/convmixer
Paper: https://arxiv.org/pdf/2201.09792v1.pdf
@Machine_learn
📹 VRT: A Video Restoration Transformer
Github: https://github.com/jingyunliang/vrt
Paper: https://arxiv.org/abs/2201.12288
Dataset: https://paperswithcode.com/dataset/gopro
@Machine_learn
Github: https://github.com/jingyunliang/vrt
Paper: https://arxiv.org/abs/2201.12288
Dataset: https://paperswithcode.com/dataset/gopro
@Machine_learn
📝 Automated Crossword Solving
Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.
Github: https://github.com/albertkx/berkeley-crossword-solver
Paper: https://arxiv.org/abs/2205.09665v1
Dataset: https://www.xwordinfo.com/JSON/
@Machine_learn
Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.
Github: https://github.com/albertkx/berkeley-crossword-solver
Paper: https://arxiv.org/abs/2205.09665v1
Dataset: https://www.xwordinfo.com/JSON/
@Machine_learn
[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral)
https://github.com/Garfield-kh/PoseTriplet
@Machine_lean
https://github.com/Garfield-kh/PoseTriplet
@Machine_lean
GitHub
GitHub - Garfield-kh/PoseTriplet: [CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under…
[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral) - Garfield-kh/PoseTriplet
📍 Perturbation Augmentation for Fairer NLP
Responsible NLP projects from Meta AI.
Github: https://github.com/facebookresearch/responsiblenlp
Paper: https://arxiv.org/abs/2205.12586v1
Dataset: https://paperswithcode.com/dataset/glue
@Machine_learn
Responsible NLP projects from Meta AI.
Github: https://github.com/facebookresearch/responsiblenlp
Paper: https://arxiv.org/abs/2205.12586v1
Dataset: https://paperswithcode.com/dataset/glue
@Machine_learn
B978-0-12-810408-8.00020-1.pdf
754.9 KB
Randomized Deep Learning Methods for Clinical Trial Enrichment and Design in Alzheimer’s Disease #Chapter15
@Machine_learn
@Machine_learn
B978-0-12-810408-8.00022-5.pdf
1.5 MB
Deep Networks and Mutual Information Maximization for Cross-Modal Medical Image Synthesis #Chapter16
@Machine_learn
@Machine_learn
B978-0-12-810408-8.00023-7.pdf
1.7 MB
Natural Language Processing for Large-Scale Medical Image Analysis Using Deep Learning
#Chapter17
@Machine_learn
#Chapter17
@Machine_learn
🦠 MaSIF- Molecular Surface Interaction Fingerprints: Geometric deep learning to decipher patterns in protein molecular surfaces.
MaSIF is a proof-of-concept method to decipher patterns in protein surfaces important for specific biomolecular interactions.
Github: https://github.com/LPDI-EPFL/masif
Paper: https://www.nature.com/articles/s41592-019-0666-6
Data: https://github.com/LPDI-EPFL/masif#MaSIF-data-preparation
@Machine_learn
MaSIF is a proof-of-concept method to decipher patterns in protein surfaces important for specific biomolecular interactions.
Github: https://github.com/LPDI-EPFL/masif
Paper: https://www.nature.com/articles/s41592-019-0666-6
Data: https://github.com/LPDI-EPFL/masif#MaSIF-data-preparation
@Machine_learn
🪄 Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmark.
Github: https://github.com/naver/kapture-localization
Paper: https://arxiv.org/abs/2205.15761v1
Data: https://paperswithcode.com/dataset/inloc
@Machine_learn
Github: https://github.com/naver/kapture-localization
Paper: https://arxiv.org/abs/2205.15761v1
Data: https://paperswithcode.com/dataset/inloc
@Machine_learn