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코드

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

https://github.com/n-akram/GradCamDDD

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/n-akram/SafeML

SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure

https://github.com/n-friederich/airport_fence_inspection

VarifocalNet: An IoU-aware Dense Object Detector

https://github.com/n-waves/multifit

A Corpus for Multilingual Document Classification in Eight Languages

https://github.com/nab-126/resnet

Unsupervised Representation Learning by Predicting Image Rotations

https://github.com/nagadomi/kaggle-cifar10-torch7

Network In Network

https://github.com/nageshsinghc4/deepwrap

Bag of Tricks for Efficient Text Classification

https://github.com/nahmiasd/DeepSign

DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification

https://github.com/naiveHobo/InvoiceNet

Attend, Copy, Parse -- End-to-end information extraction from documents

https://github.com/nalbarr/coursera-ai4med-course3

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/nalexai/hyperlib

Hyperbolic Image Embeddings

https://github.com/namtpham/image_tampering_detection_references

Detection and Localization of Image Forgeries using Resampling Features and Deep Learning

https://github.com/narutomst/Auto-CNN-HSI-Classification

DARTS: Differentiable Architecture Search

https://github.com/natel9178/transformer-refork

A Structured Self-attentive Sentence Embedding

https://github.com/natgable/cs-229-project

Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural Networks

https://github.com/nathanin/IIC

Invariant Information Clustering for Unsupervised Image Classification and Segmentation

https://github.com/native2019/hello

YOLO9000: Better, Faster, Stronger

https://github.com/nautilus261/tf-faster-rcnn

An Implementation of Faster RCNN with Study for Region Sampling

https://github.com/naver-ai/vidt

IoU-aware Single-stage Object Detector for Accurate Localization

https://github.com/naver/tldr

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

https://github.com/navganti/SIVO

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/navganti/SegNet

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/navodhya/DMN

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing

https://github.com/nazmul-karim170/NFT-Augmented-Backdoor-Purification

VideoMix: Rethinking Data Augmentation for Video Classification

https://github.com/ncbi-nlp/BLUE_Benchmark

ML-Net: multi-label classification of biomedical texts with deep neural networks

https://github.com/ncbi-nlp/ML_Net

ML-Net: multi-label classification of biomedical texts with deep neural networks

https://github.com/ncbi-nlp/NegBio

ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

https://github.com/nchungvh/dlcl

Associative Domain Adaptation

https://github.com/nctumllab/huang-ching-wei

The Variational Fair Autoencoder

https://github.com/nealgravindra/self-supervsed_edge_feats

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks

https://github.com/neburseni/NLP

Universal Language Model Fine-tuning for Text Classification

https://github.com/neerajvashistha/vgg16

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/negarhdr/PGCN

Semi-Supervised Classification with Graph Convolutional Networks

https://github.com/negu93/cvnn-polsar

Pixel-Wise PolSAR Image Classification via a Novel Complex-Valued Deep Fully Convolutional Network

https://github.com/neil-zeng/asr

Advances in Joint CTC-Attention based End-to-End Speech Recognition with a Deep CNN Encoder and RNN-LM

https://github.com/nestle1993/SE16-Task6-Stance-Detection

Convolutional Neural Networks for Sentence Classification

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