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General Classification

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/hantek/deeplearn_hsi

공식 코드

Spectral-Spatial Classification of Hyperspectral Image Using Autoencoders

https://github.com/hantek/zlinnet

공식 코드

How far can we go without convolution: Improving fully-connected networks

https://github.com/haofanwang/accurate-head-pose

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Hybrid coarse-fine classification for head pose estimation

https://github.com/haoheliu/diffres-python

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Learning Temporal Resolution in Spectrogram for Audio Classification

https://github.com/haoming-codes/str-withheld

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Classification with Strategically Withheld Data

https://github.com/haoyelyu/On_the_Dynamics_of_Training_Attention_Models

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On the Dynamics of Training Attention Models

https://github.com/haozhenWu/Calibrated-Boosting-Forest

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Calibrated Boosting-Forest

https://github.com/happinesslz/EPNet

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EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection

https://github.com/haroonshakeel/bilingual_sms_classification

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A Multi-cascaded Deep Model for Bilingual SMS Classification

https://github.com/haroonshakeel/multisenti

공식 코드

Adapting Deep Learning for Sentiment Classification of Code-Switched Informal Short Text

https://github.com/hasanhuz/SpanEmo

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SpanEmo: Casting Multi-label Emotion Classification as Span-prediction

https://github.com/hasibzunair/adversarial-lesions

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Melanoma Detection using Adversarial Training and Deep Transfer Learning

https://github.com/hassounlab/EPP

공식 코드

Enzyme promiscuity prediction using hierarchy-informed multi-label classification

https://github.com/hbilen/WSDDN

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Weakly Supervised Deep Detection Networks

https://github.com/hchoi71/AMC-Loss

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AMC-Loss: Angular Margin Contrastive Loss for Improved Explainability in Image Classification

https://github.com/heaventian93/MDAIR

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Modified Distribution Alignment for Domain Adaptation with Pre-trained Inception ResNet

https://github.com/hechtlinger/graph_cnn

공식 코드

A Generalization of Convolutional Neural Networks to Graph-Structured Data

https://github.com/heimingx/pcm

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Progressive Class Semantic Matching for Semi-supervised Text Classification

https://github.com/hellowangqian/multi-label-image-classification

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A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural Networks

https://github.com/hendraet/handwriting-classification

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Handwriting Classification for the Analysis of Art-Historical Documents

https://github.com/hendrycks/pre-training

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Using Pre-Training Can Improve Model Robustness and Uncertainty

https://github.com/henrygouk/stochastic-gradient-trees

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Stochastic Gradient Trees

https://github.com/henrylee2570/NoisyAnchor

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Learning from Noisy Anchors for One-stage Object Detection

https://github.com/henrymoss/COLING2018

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Using J-K fold Cross Validation to Reduce Variance When Tuning NLP Models

https://github.com/hessamb/label-refinery

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Label Refinery: Improving ImageNet Classification through Label Progression

https://github.com/hextrato/KER

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Evaluating the Effectiveness of Margin Parameter when Learning Knowledge Embedding Representation for Domain-specific Multi-relational Categorized Data

https://github.com/hezhangsprinter/SROSR

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Sparse Representation-based Open Set Recognition

https://github.com/hfawaz/InceptionTime

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InceptionTime: Finding AlexNet for Time Series Classification

https://github.com/hfawaz/aaltd18

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Data augmentation using synthetic data for time series classification with deep residual networks

https://github.com/hfawaz/bigdata18

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Transfer learning for time series classification

https://github.com/hfawaz/dl-4-tsc

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Deep learning for time series classification: a review

https://github.com/hfawaz/ijcars19

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Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks

https://github.com/hfawaz/ijcnn19attacks

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Adversarial Attacks on Deep Neural Networks for Time Series Classification

https://github.com/hfawaz/ijcnn19ensemble

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Deep Neural Network Ensembles for Time Series Classification

https://github.com/hfawaz/miccai18

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Deep learning for time series classification

https://github.com/hhcho/hyplinear

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Large-Margin Classification in Hyperbolic Space

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.