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Improving Efficiency in Large-Scale Decentralized Distributed Training https://deepai.org/publication/improving-efficiency-in-large-scale-decentralized-distributed-training … by
@vee0vee et al.#ComputerVision#ImageNet -
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I Am Bless and Happy Because . first time ko nilibre si mama
@imninotch sa kanyang favorite na japanese restaurant sa *#Tsurumaruudonxtempura gamit ang aking unang 13th month pay sa aking first Job sa#imagenet

pic.twitter.com/vAvjVFZ9QN
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Semantic Adversarial Perturbations using Learnt Representations https://deepai.org/publication/semantic-adversarial-perturbations-using-learnt-representations … by Isaac Dunn et al.
#Classifier#ImageNet -
Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks GitHub: https://github.com/AdamByerly/HVCsEnableAGD …
#NeuralNetwork#ConvolutionalNeuralNetwork#ImageNet#ImageClassification -
Level up your data science vocabulary: ImageNet https://deepai.org/machine-learning-glossary-and-terms/imagenet …
#ImageNet -
#FAT2020 paper: "Towards fairer datasets: filtering and balancing the distribution of the people subtree in the#ImageNet hierarchy" going from 2832 people labels to only 159 "safe" and "imageable" labels... https://doi.org/10.1145/3351095.3375709 …pic.twitter.com/KOL02N0Jt0
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CSNNs: Unsupervised, Backpropagation-free Convolutional Neural Networks for Representation Learning https://deepai.org/publication/csnns-unsupervised-backpropagation-free-convolutional-neural-networks-for-representation-learning … by Bonifaz Stuhr et al.
#ImageNet#ConvolutionalNeuralNetworks -
Artificial Intelligence Can Insult, Curse, Hurl Racial Slurs http://dld.bz/hTACb
#AI#artificialintelligence#facialrecognition#algorithms#ImageNet#Stanford#debiasing#bias#prejudices -
Why is
#ImageNet considered such a major turning point in deep learning? Our latest blog dives into our collaboration with Alectio to develop processes to improve the quality of any training set, and eventually, train better models with less data. http://ow.ly/1x4t50y7nsq -
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation https://deepai.org/publication/on-last-layer-algorithms-for-classification-decoupling-representation-from-uncertainty-estimation … by Nicolas Brosse et al.
#DeepLearning#ImageNet -
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation https://deepai.org/publication/cross-domain-few-shot-classification-via-learned-feature-wise-transformation … by Hung-Yu Tseng et al. including
@jbhuang0604#ImageNet#ComputerScience -
"GI needs its own
#imagenet". ImageNet =1.2 million images of >1000 categories, incl “tree”, “tool”, & “tractor”.. This is used as 'pre-training' for medical#AI algorithms(!)@FvdSommen suggests GI-specific pre-training may
performance for endo #AI. http://jmai.amegroups.com/article/view/5213/html …pic.twitter.com/Lpq0F1JkXH
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Towards detection and classification of microscopic foraminifera using transfer learning https://deepai.org/publication/towards-detection-and-classification-of-microscopic-foraminifera-using-transfer-learning … by Thomas Haugland Johansen et al.
#DeepLearning#ImageNet -
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise https://deepai.org/publication/increasing-the-robustness-of-dnns-against-image-corruptions-by-playing-the-game-of-noise … by Evgenia Rusak et al. including
@matthiasbethge#ImageNet#ComputerScience -
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation https://deepai.org/publication/noisy-machines-understanding-noisy-neural-networks-and-enhancing-robustness-to-analog-hardware-errors-using-distillation … by Chuteng Zhou et al. including
@PradKadambi#MachineLearning#ImageNet -
I totally agree with
@FvdSommen conclusions in http://jmai.amegroups.com/article/view/5213/html#B21 …. We need specific datasets like#imagenet for#medicine. For GI endoscopy we published just recently an open dataset that tries to be the first step towards this: http://osf.io/mh9sj/#AI -
Trends in Machine/Deep Learning w/ Zack Lipton
Premises & Hypothesis
Transformers instead of LSTM
Invariant Risk Minimization
Generative VS Discriminative Models
#imagenet
Zack @zacharylipton@CarnegieMellon
Sam @samcharrington
@twimlaihttps://twimlai.com/twiml-talk-334-trends-in-machine-learning-deep-learning-with-zack-lipton … -
In 2019 a webapp called
#ImageNetRoulette resulted in many social media posts of people tagged as criminal or gender stereotypes. It shows the importance of fighting bias in#AI. Hence, it is good to see that#ImageNet gets a label update.#responsibleai#aiforgood -
The latest
@deeplearningai_ newsletter is just amazing. The part that I liked the most is the#ImageNet dataset is being modified and efforts are being made to purge the bias outta it. Read the jam-packed newsletter here: https://blog.deeplearning.ai/blog/the-batch-facebook-takes-on-deepfakes-google-ai-battles-cancer-researchers-fight-imagenet-bias-ai-grows-globally ….
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