publicações selecionadas
- Interactive machine learning for soybean seed and seedling quality classification
- Quality classification of Jatropha curcas seeds using radiographic images and machine learning
- Deep learning-based approach using X-ray images for classifying Crambe abyssinica seed quality
- GERMINATION AND POST-SEMINAL DEVELOPMENT OF Melaleuca alternifolia (MAIDEN & BETCHE) CHEEL
- Physical and physiological quality of Jatropha curcas L. seeds at different maturity stages using image analysis
- Weathering deterioration in pre-harvest of soybean seeds: physiological, physical, and morpho-anatomical changes
- IJCropSeed: An open-access tool for high-throughput analysis of crop seed radiographs
- ASSESSMENT OF THE PHYSICAL AND PHYSIOLOGICAL QUALITY OF Piptadenia gonoacantha SEEDS (MART.) J. F. MACBR. USING IMAGE ANALYSIS
- NON-DESTRUCTIVE IDENTIFICATION OF PHYSICAL DAMAGE IN MUNG BEAN (Vigna radiata L.) SEEDS BY X-RAY IMAGE ANALYSIS IDENTIFICAÃ?Ã?O NÃ?O DESTRUTIVA DE DANOS FÃ?SICOS EM SEMENTES DE FEIJÃ?O MUNGO (Vigna radiata L.) POR ANÃ?LISE DE IMAGEM
- Chickpea seed vigor evaluated by computerized seedling analysis
- X-ray imaging and digital processing application in non-destructive assessing of melon seed quality
- High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images