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Image Segmentation in Aerial Imagery: A Review Ade Purwanto; Dewi Habsari Budiarti; Fithri Nur Purnamastuti; Irfansyah Yudhi Tanasa; Yomi Guno; Aris Surya Yunata; Mukti Wibowo; Asyaraf Hidayat; Dede Dirgahayu
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.006

Abstract

The problem of distinguishing objects has plagued researchers for many years because of low accuracy compared to human eyes’ capability. In the last decade, the use of Machine Learning in aerial imagery data processing has multiplied, with the technology behind it has also developed exponentially. One of those technologies is image-based object identification, which relies heavily upon data computation. To reduce the computational load, various data segmentation algorithm was developed. This study is focused on reviewing the various image segmentation technology in aerial imagery for image recognition. Literature from as far as 1981 from various journals and conferences worldwide was reviewed. This review examines specific research questions to analyze image segmentation research over time and the challenges researchers face with each method. Machine Learning has gained popularity among segmentation methods. However, Deep Learning has been aggressively put an essential role in it by overcoming many of its weaknesses. The advanced algorithm used in Deep Learning to process the segmentation may drive more efficient and accurate data processing. 
INOCULATION TECHNIQUE OF COLLETOTRICHUM GLOEOSPORIOIDES AFFECTS Phyllanthus niruri L. GROWTH AND BIOACTIVE COMPOUND SYNTHESIS Irna Surya Bidara; Siti Himawati; Eka Nurhangga; Yomi Guno; Winda Nawfetrias
Gunung Djati Conference Series Vol. 66 (2026): The International Conference on Perennial Crops 2026
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/gdcs.v66i.3414

Abstract

Colletotrichum gloeosporioides, an endophytic fungus, significantly enhances growth, defense against pathogens, and remediation of environmental stress in medicinal plants through induced resistance and phytohormone synthesis. The application technique affects the fungi's effectiveness in stimulating growth and inducing bioactive compounds in plants. Phyllanthus niruri is an Indonesian medicinal plant with bioactive compounds like flavonoids, alkaloids, terpenoids, lignans, polyphenols, tannins, and saponins. They offer health benefits like antioxidant, anti-inflammatory, analgesic, and antiviral effects. However, research on Phyllanthus-endophytic fungi from the Colletotrichum has not been reported. This study proposes that the application technique used for C. gloeosporioides affects the fungi's effectiveness in stimulating plant growth and inducing beneficial bioactive compounds. We experimented during 2022 and 2023 at an experimental greenhouse with two different methods of fungi inoculation: seed and planting medium. The study reveals that C. gloeosporioides inoculation impacts P. niruri growth differently, with seed inoculation promoting growth and planting medium inoculation potentially hindering it. Metabolic profiling through clustering analysis indicates that fungal inoculation significantly alters the plant's chemical composition, particularly increasing the abundance of specific alkenes, suggesting activation of defense mechanisms involving very long-chain fatty acids. It highlights the critical role of the inoculation method in shaping plant-microbe interactions and influencing the production of pharmacologically relevant compounds like steroids, diketones, alkanes, and alkenes, which may serve in the plant's defense responses and have beneficial impacts on human health. Therefore, optimizing inoculation strategies and understanding the underlying biological mechanisms are crucial for harnessing the potential benefits of microbial inoculants in agriculture and biotechnology.