Ali, AkbarAkbarAliVyas, MahekMahekVyasDebnath, SoumyaratnaSoumyaratnaDebnathKamra, Chanda GroverChanda GroverKamraKhalane, Jaidev SanjayJaidev SanjayKhalaneDevanesan, Reuben ShibuReuben ShibuDevanesanMastan, Indra DeepIndra DeepMastanSankaranarayanan, SubramanianSubramanianSankaranarayananKhanna, PankajPankajKhannaRaman, ShanmuganathanShanmuganathanRaman2025-10-132025-10-132025-09-1410.1109/ICIP55913.2025.110847342-s2.0-105028565531https://repository.iitgn.ac.in0/handle/IITG2025/33144This paper presents COT-AD, a comprehensive Dataset designed to enhance cotton crop analysis through computer vision. Comprising over 25,000 images captured throughout the cotton growth cycle, with 5,000 annotated images, COT-AD includes aerial imagery for field-scale detection and segmentation and high-resolution DSLR images documenting key diseases. The annotations cover pest and disease recognition, vegetation, and weed analysis, addressing a critical gap in cotton-specific agricultural datasets. COT-AD supports tasks such as classification, segmentation, image restoration, enhancement, deep generative model-based cotton crop synthesis, and early disease management, advancing data-driven crop management .The COT-AD dataset can be found here:https://aamaanakbar.github.io/COT-AD/.en-USCotton Crop DatasetCrop MonitoringPrecision FarmingConference Paper0123456789/433