Proceedings
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| Filter results13 paper(s) found. |
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1. Color Identification and Texture Features of Phalaenopsis Using Deep LearningAs one of the most economically important and widely traded ornamental plants worldwide, Phalaenopsis hold a significant position in the global floriculture industry. The breeding process is traditionally labor-intensive, requiring careful visual assessment of numerous floral traits to select desirable varieties, which underscores the need for scalable, automated solutions. To enhance the efficiency of Phalaenopsis breeding and accelerate phenotypic comparison across varieties,... Y. Kuo |
2. Lauraceae Timber Identification Using Vision TransformerThe forest coverage in Taiwan exceeds 60%, yet over 99% of annual timber consumption relies on imports. This significant dependence, coupled with frequent incidents of wood misidentification and fraud, highlights the need for accurate and efficient wood species identification systems. Conventional approaches, such as microscopic analysis and sensory- based macroscopic inspection, are labor-intensive, subjective, and require domain expertise, making them unsuitable for large-scale or real-time... Y. Kuo |
3. Dual-channel Imaging and Two-stage Deep Learning for Fertility Detection of Duck EggsIn Taiwan, the waterfowl industry generates a production value of NT$11.2 billion, of which meat ducks contribute about 80% (≈NT$8.9 billion). As the upstream segment of the duck meat industry, the hatching process of duck eggs plays a critical role in duck production. Fertilized eggs require a clean incubation environment to develop properly. To protect this environment, unfertilized eggs need to be removed at an early stage, which makes fertility detection essential. However, conventional candling... Y. Kuo |
4. Applying Retrieval-augmented-generation to Support Farmers in Pest and Disease DiagnosisAccording to the Ministry of Agriculture, crop production in Taiwan reached a value of $275 billion NTD in 2023, highlighting the economic importance of agriculture. However, the industry is now facing serious challenges, particularly in pest and disease identification and crop protection. Due to global ecological challenges, the manifestations of local pests and diseases have changed, making it difficult for farmers to rely on past experiences to identify and manage them effectively. Farmers... Y. Kuo |
5. Nighttime Piglet Detection Using Deep LearningIn 2023, Taiwan’s pig industry was valued at over NT$85.1 billion, representing nearly 40% of total livestock production. However, effective piglet management remains a challenge due to environmental variability, frequent aggressive behaviors, and labor shortages—especially during nighttime. Traditional monitoring methods rely on manual observation, which is time-consuming, subjective, and impractical for continuous surveillance. To address this, we propose an automated nighttime piglet... Y. Kuo |
6. Phalaenopsis Seedling Assessment Using Leaf Contour Detection with YOLOIn this study, we propose a vision-based approach for automatically measuring the morphological traits of Phalaenopsis seedlings. By utilizing top-view and side-view images, our method automatically extracts leaf contours to replace traditional manual measurements. A YOLOv8n-seg model was employed to segment the seedlings, and further correction strategies were introduced to improve accuracy. Experimental results demonstrate the potential of our approach to support large-scale seedling classification... Y. Kuo |
7. Automated Identification of Tomato Diseases, Pests, and Disorders Using Ai Models and Smartphone ApplicationsTomato is one of the most important economic crops in many countries, with a substantial global production volume. However, tomato growth is often affected by diseases, pests, and physiological disorders (DPD), which typically manifest as symptoms on leaves, such as specks, yellowing, necrosis, or leaf deformation. These issues significantly reduce tomato yield and quality. Therefore, accurately identifying these symptoms and implementing corresponding management strategies have become crucial.... Y. Kuo |
8. Detecting and Removing Defective Carcasses of Taiwanese Native Chickens Using Convolutional Neural NetworksPoultry is one of the most important sources of meat worldwide. In 2023, the production value of poultry in Taiwan reached 59.8 billion NTD, accounting for 27.8% of the economic value of the animal husbandry industry. Among various chicken breeds, Taiwanese native chickens (TNC) are highly favored by consumers for their meat quality and flavor. As the demand for chicken increases, providing high quality meat to the market has become crucial. Unlike broilers, Taiwanese native chickens have diverse... Y. Kuo |
9. Identification of Citrus Diseases, Pests, and Disorders Using Deep LearningTaiwan’s warm climate offers favorable conditions for citrus production, making it the most economically valuable fruit crop in the country. Citrus trees are perennial and mainly propagated asexually. Long-term exposure and limited genetic diversity make them more susceptible to infection by various pathogens. In practice, diagnosis often relies on farmers’ experience, which can be subjective despite their familiarity with local conditions. Microscopic examination by plant pathologists... Y. Kuo |
10. Automatic Counting of Chickens Around Feeders Using Convolutional Neural NetworksIn 2023, Taiwan’s chicken industry generated about NTD 93.6 billion, or 43.5% of the livestock production value, underscoring its central role in the sector. Nonetheless, monitoring flock health and housing remains labor-intensive, and adjustments to feeding regimes frequently depend on subjective judgment, limiting standardization and scalability. Because feeding behavior is a key indicator of health and welfare, we present a vision-based system that continuously detects feeders and counts... Y. Kuo |
11. Automated Selection of Taiwan Native Breeding Chickens Using Machine Vision and Deep LearningChicken is a primary global source of protein. In Taiwan, the poultry sector is a cornerstone of the domestic food supply. A significant part of this sector is the Taiwan Native Chicken (TNC), a collection of indigenous breeds prized for their unique flavor and cultural value, generating over 26 billion New Taiwan Dollars in 2023. Maintaining the quality of TNC relies on the effective selection of superior breeders. Conventionally, this selection is performed through manual inspection of phenotypic... Y. Kuo |
12. Identification of Cucumber Pests, Diseases, and Disorders Using Deep LearningCucumber is an essential economic crop worldwide, which is typically cultivated in summer. The hot and humid conditions make them highly susceptible to various pests, diseases, and physiological disorders, which hinder their growth and lead to significant yield losses. Early and accurate detection is vital to limiting the spread of diseases or pests. However, traditional diagnostic approaches rely heavily on visual inspection by experienced farmers or microscopic examination by specialists, which... Y. Kuo |
13. Monitoring Chicken Houses with AI Surveillance SystemIn Taiwan, the need of chicken meat accounts for approximately 30% of total livestockvproduction. In order to maintaining animal welfare, floor-rearing chicken farming approaches are widely used in Taiwan. However, traditional poultry management is often labor-intensive which increases the risk of disease transmission. To improve monitoring efficiency, we proposed a smart rail surveillance system to automatically monitor chickens for real-time chicken health assessment. The system comprised a... Y. Kuo |