Specificity
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/SAIL-GuoLab/Cell_Segmentation_and_Tracking
공식 코드https://github.com/Sajib-006/Patho-LM
공식 코드PathoLM: Identifying pathogenicity from the DNA sequence through the Genome Foundation Model
https://github.com/SasCezar/GitHubClassificationDataset
공식 코드GitRanking: A Ranking of GitHub Topics for Software Classification using Active Sampling
https://github.com/SciCrunch/Antibody-Watch
공식 코드Antibody Watch: Text Mining Antibody Specificity from the Literature
https://github.com/ShahinSHH/COVID-CAPS
공식 코드COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images
https://github.com/ShahinSHH/COVID-FACT
공식 코드https://github.com/ShahinSHH/CT-CAPS
공식 코드https://github.com/SimonThomine/FABLE
공식 코드https://github.com/Sootung/RAMer
공식 코드https://github.com/StatPhysBio/tcr_antigen_design
공식 코드T-cell receptor specificity landscape revealed through de novo peptide design
https://github.com/Stefan-Yu404/MP-UNet
공식 코드https://github.com/Tinard/dnagcn
공식 코드DNA-GCN: Graph convolutional networks for predicting DNA-protein binding
https://github.com/Windbelll/Prognosis-analysis-of-cerebral-hemorrhage
공식 코드https://github.com/YalongLiu/Refined-Segmentation-R-CNN
공식 코드https://github.com/YalongLiu/Trident-Segmentation-CNN
공식 코드https://github.com/YossiZhao/CwA-T
공식 코드CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality Detection
https://github.com/ZFTurbo/DrivenData-Alzheimer-Research-1st-place-solution
공식 코드3D Convolutional Neural Networks for Stalled Brain Capillary Detection
https://github.com/ZFTurbo/classification_models_3D
공식 코드3D Convolutional Neural Networks for Stalled Brain Capillary Detection
https://github.com/ZFTurbo/volumentations
공식 코드3D Convolutional Neural Networks for Stalled Brain Capillary Detection
https://github.com/aerosonicdb/aerosonicdb-ypad0523
공식 코드The AeroSonicDB (YPAD-0523) Dataset for Acoustic Detection and Classification of Aircraft
https://github.com/ahmadtaheri2021/federated-deep-learning
공식 코드https://github.com/ahmadtaheri2021/lithology-microscopic-images-mini-dataset
공식 코드https://github.com/ai-forever/ghost
공식 코드A new face swap method for image and video domains: a technical report
https://github.com/aikunyi/amplifier
공식 코드Amplifier: Bringing Attention to Neglected Low-Energy Components in Time Series Forecasting
https://github.com/aimagelab/open-fashion-clip
공식 코드OpenFashionCLIP: Vision-and-Language Contrastive Learning with Open-Source Fashion Data
https://github.com/akabircs/skin-lesions-classification
공식 코드An Attention-Guided Deep Learning Approach for Classifying 39 Skin Lesion Types
https://github.com/akhila-yerukola/normad
공식 코드NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Models
https://github.com/alestolfo/lm-arithmetic
공식 코드https://github.com/alexander-rakhlin/ICIAR2018
공식 코드Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
https://github.com/alexduvalinho/geometric-gnns
공식 코드A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems
https://github.com/alibaba-damo-academy/pixel-lesion-patient-network
공식 코드Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network
https://github.com/allenai/marg-reviewer
공식 코드https://github.com/alonhzn/testauc
공식 코드https://github.com/alps-lab/trojan-lm
공식 코드https://github.com/alsayyahi/timeline
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.