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2D Classification

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

https://github.com/Rokken-lab6/Failure-Analysis-and-Model-Repairment

공식 코드

A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging

https://github.com/RomeroCode/towards-network-data-analytics-in-5g

공식 코드

Towards Network Data Analytics in 5G Systems and Beyond

https://github.com/Rongjiehuang/GenerSpeech

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GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech

https://github.com/RoyalVane/ASM

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Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation

https://github.com/Royalvice/DocDiff

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DocDiff: Document Enhancement via Residual Diffusion Models

https://github.com/Ruiyang-061X/UA3D

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Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection

https://github.com/RunpeiDong/DGMS

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Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks

https://github.com/RuoyuChen10/CCL-FSOD

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Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detection

https://github.com/RyanXLi/OneshotDet

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One-Shot Object Detection without Fine-Tuning

https://github.com/SALT-NLP/demonstrated-feedback

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Aligning Language Models with Demonstrated Feedback

https://github.com/SDPRA-2021/shared-task

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Using Transformer based Ensemble Learning to classify Scientific Articles

https://github.com/SDPRA-2021/shared-task/tree/main/FideLIPI

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Using Transformer based Ensemble Learning to classify Scientific Articles

https://github.com/SFIG611/tabbie

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TABBIE: Pretrained Representations of Tabular Data

https://github.com/SHI-Labs/Convolutional-MLPs

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ConvMLP: Hierarchical Convolutional MLPs for Vision

https://github.com/SHI-Labs/Neighborhood-Attention-Transformer

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Neighborhood Attention Transformer

https://github.com/SHI-Labs/Pseudo-IoU-for-Anchor-Free-Object-Detection

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Pseudo-IoU: Improving Label Assignment in Anchor-Free Object Detection

https://github.com/SHI-Labs/Rethinking-Text-Segmentation

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Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

https://github.com/SHIDCenter/PathoNet

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PathoNet: Deep learning assisted evaluation of Ki-67 and tumor infiltrating lymphocytes (TILs) as prognostic factors in breast cancer; A large dataset and baseline

https://github.com/SIAnalytics/RHINO

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Hausdorff Distance Matching with Adaptive Query Denoising for Rotated Detection Transformer

https://github.com/SJTU-Det/R3Det_Tensorflow

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R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

https://github.com/SJTU-LuHe/TransVOD

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End-to-End Video Object Detection with Spatial-Temporal Transformers

https://github.com/SJTU-Thinklab-Det/DOTA-DOAI

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SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing

https://github.com/SJTU-Thinklab-Det/OHDet_Tensorflow

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On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited

https://github.com/SJTU-Thinklab-Det/r3det-on-mmdetection

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R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

https://github.com/SJoJoK/3DGStream

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3DGStream: On-the-Fly Training of 3D Gaussians for Efficient Streaming of Photo-Realistic Free-Viewpoint Videos

https://github.com/SLDGroup/GreedyViG

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GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs

https://github.com/SLWZwaard/DMT

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Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink Conditioning

https://github.com/SPOClab-ca/writing-features-AI-papers

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What do writing features tell us about AI papers?

https://github.com/SS47816/AGI-Elo

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AGI-Elo: How Far Are We From Mastering A Task?

https://github.com/STVIR/Grid-R-CNN

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Grid R-CNN Plus: Faster and Better

https://github.com/SYangDong/tse-t

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Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection

https://github.com/SaadUllahAkram/CellTracker

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Cell Tracking via Proposal Generation and Selection

https://github.com/Sagarika-Singh-99/indonesian_manhwa_translation

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Crossing Language Borders: A Pipeline for Indonesian Manhwa Translation

https://github.com/SaiedAlshahrani/leveraging-corpus-metadata

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Leveraging Corpus Metadata to Detect Template-based Translation: An Exploratory Case Study of the Egyptian Arabic Wikipedia Edition

https://github.com/SaliencyMix/SaliencyMix

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SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization

https://github.com/Scalsol/RepPointsV2

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RepPoints V2: Verification Meets Regression for Object Detection

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