Seminar 2020
Deformable DETR.pdfDeformable DETR: Deformable Transformers for End-to-End Object Detection
Deformable DETR: Deformable Transformers for End-to-End Object Detection
ArcFace_Review.pdfArcFace: Additive Angular Margin Loss for Deep Face Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Distiling the knowledge in neural network.pdfDistilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
DeepLab_seminar.pdfDeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
AutoML-Zero Review.pdfAutoML-Zero: Evolving Machine Learning Algorithms From Scratch
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
GRU 세미나.pdfGRU: Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
GRU: Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Attention based CNN-ConvLSTM_by박희찬.pdfAttention Based CNN-ConvLSTM for Pedestrian Attribute Recognition
Attention Based CNN-ConvLSTM for Pedestrian Attribute Recognition
A Closer Look at Spatiotemporal_byKangHee.pdfA Closer Look at Spatiotemporal Convolutions for Action Recognition
A Closer Look at Spatiotemporal Convolutions for Action Recognition
The electronic nose technology in clinical diagnosis A systematic review_bySeongWu.pdfThe Electronic Nose Technology in Clinical Diagnosis: A systematic review
The Electronic Nose Technology in Clinical Diagnosis: A systematic review
Mask R-CNN.pdfMask R-CNN
Mask R-CNN
U-Net_seminar.pdfU-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Recurrent Nets that Time and Count_byJinWon.pdfRecurrent Nets that Time and Count
Recurrent Nets that Time and Count
FaceNet_review.pdfFaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Bootstrap Your Own Latent.pdfBootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Efficient Neural Architecture Search via Parameter Sharing
Efficient Neural Architecture Search via Parameter Sharing
M-NET_3D_segmentaion.pdfM-NET: A Convolutional Neural Network For Deep Brain Structure Segmentation
M-NET: A Convolutional Neural Network For Deep Brain Structure Segmentation
Resnet_byJeongHo.pdfDeep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
rethink 이강희.pdfUnderstanding deep learning requires rethinking generalization
Understanding deep learning requires rethinking generalization
Synthesizer - 박희찬.pdfSynthesizer: Rethinking Self-Attention in Transformer Models with Natural Language Processing
Synthesizer: Rethinking Self-Attention in Transformer Models with Natural Language Processing
Attention Is All You Need - 박희찬.pdfAttention Is All You Need
Attention Is All You Need
Pruning Filters_by변성우.pdfPruning Filters for Efficient ConvNets
AlexNet_byJinWon.pdfImageNet Classification with Deep Convolutional Neural Networks
Regnet_by김현일.pdfDesigning Network Design Spaces
Designing Network Design Spaces
dynamic routing.pdfDynamic Routing Between Capsules
Fixing the train-test resolution discrepancy.pdfFixing the train-test resolution discrepancy
ResNet_byJinWon.pdfDeep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
DCL발표자료.pdfDynamic Curriculum Learning for Imbalanced Data Classification
Dynamic Curriculum Learning for Imbalanced Data Classification
cbam_by이강희.pdfCBAM : Convolutional Block Attention Module
CBAM : Convolutional Block Attention Module
EfficientDet_by김현일.pdfEfficientDet: Scalable and Efficient Object Detection
EfficientDet: Scalable and Efficient Object Detection