Kumar Abhishek @__KumarAbhishek
PhD Student, Medical Image Analysis Lab, Simon Fraser University sfu.ca/~kabhishe/ Vancouver, Canada Joined July 2012-
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Kumar Abhishek retweeted
📢🏆Congrats to Kumar Abhishek for winning Best Paper at 2024 MICCAI Skin Image Analysis workshop for his Segmentation Style Discovery work (with Jeremy Kawahara), with Application to Skin Lesion Image. @SFU_CompSci 📄 cs.sfu.ca/~hamarneh/ecop… 💻 github.com/sfu-mial/Style…
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Kumar Abhishek retweeted
📢 New paper on Multi-Sample ζ-mixup accepted to the Journal of Big Data @__KumarAbhishek @latent_features Colin J Brown @SFU_CompSci PDF i.sfu.ca/sYMpAu Video (MIDL2023) youtu.be/K1Y8kMdaqjo Poster (MIDL 2023) 2023.midl.io//virtual/poste… GitHub github.com/kakumarabhishe…
I am happy to share that my research has been cited 1,000 times according to Google Scholar! 🙂 scholar.google.com/citations?user…
Kumar Abhishek retweeted
# on shortification of "learning" There are a lot of videos on YouTube/TikTok etc. that give the appearance of education, but if you look closely they are really just entertainment. This is very convenient for everyone involved : the people watching enjoy thinking they are…
Kumar Abhishek retweeted
Just had a fantastic reunion at a conference with @NassirNavab so thrilled to have this opportunity to meet him at #MICCAI2023 @MICCAI_Society #qurit
MIAL @Hamarneh_MIA members, past and present, at #MICCAI2023.
If you are attending @midl_conference, please come by our poster S098 tomorrow at 8 AM: "ζ-mixup: Richer, More Realistic Mixing of Multiple Images". Paper: openreview.net/forum?id=iXjsA… Video: youtube.com/watch?v=K1Y8kM… Poster: 2023.midl.io/papers/s098
Kumar Abhishek retweeted
@midl_conference: @__KumarAbhishek, @ghamarneh , @Hamarneh_MIA proposed a data augmentation method, $\zeta$-mixup, that generates more diverse and realistic training samples for deep learning models compared to mixup and CutMix. #ChatGPT #dalle
Kumar Abhishek retweeted
We're pleased to announce DermSynth3D, a computational framework for synthesizing in-the-wild images of skin lesions with rich multi-task dense annotations Video: youtu.be/x3gDBJCI_3kv @SFU_CompSci 1/n
Our work on a skin tone-invariant disease classification method was presented at the @eccvconf @ISICArchive workshop last month. Paper: arxiv.org/abs/2208.13528 Code: github.com/sfu-mial/CIRCLe @ArezouPKZ @ghamarneh @SFU_CompSci #MedicalImaging #DeepLearning #Bias #Fairness #AI
Our work on a skin tone-invariant disease classification method was presented at the @eccvconf @ISICArchive workshop last month. Paper: arxiv.org/abs/2208.13528 Code: github.com/sfu-mial/CIRCLe @ArezouPKZ @ghamarneh @SFU_CompSci #MedicalImaging #DeepLearning #Bias #Fairness #AI
Kumar Abhishek retweeted
Congratulations to Zahra Mirikharaji for successfully defending her PhD thesis on #DeepLearning for #Skin Lesion #Segmentation Thanks to the supervisory & examining committee: Profs. Jinman Kim, @greg_mori, @ManolisSavva, & Mo Chen Zahra's thesis contributions include...🧵
Kumar Abhishek retweeted
Check out @__KumarAbhishek’s work on Mask2Lesion, GAN-based paired image translation approach for synthesizing skin lesion images from binary segmentation masks PDF i.sfu.ca/LUhhrR Code i.sfu.ca/fHuinm #MedicalImageAnalysis #DeepLearning #Dermatology @SFU_CompSci
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