用人脸识别思路自动分辨小鸡性别，不伤鸡、无需专家。
Facial Chick Sexing: An Automated Chick Sexing System From Chick Facial Image
- 借鉴人臉性別識別技術，通過小雞面部圖像判斷性別。
- 在兩組數據上達到81.89%準確率，具實際應用潛力。
- 適合禽類養殖場與動物福利關注者使用。
小雞性別鑒定是家禽產業中的關鍵任務，因雌雄在生產中角色不同。傳統方法如羽色和翼羽鑒定僅適用特定品種，而肛門鑒定則具有侵入性且需專業訓練。為解決這些問題，我們提出一種受人類面部性別分類啟發的新方法：面部小雞鑒定。該方法無需專家知識，旨在縮短培訓時間並提升動物福利，減少對小雞的操控。我們開發了包含數據收集、面部與關鍵點檢測、面部對齊及分類的完整系統。在兩組圖片數據（裁剪全臉與裁剪中段臉）上進行評估，均保留小雞面部關鍵特徵。實驗表明，該方法具有良好的可行性，最終準確率達81.89%，未來有望實現更普適的小雞性別鑒定。
原文摘要 · Abstract (English)
Chick sexing, the process of determining the gender of day-old chicks, is a critical task in the poultry industry due to the distinct roles that each gender plays in production. While effective traditional methods achieve high accuracy, color, and wing feather sexing is exclusive to specific breeds, and vent sexing is invasive and requires trained experts. To address these challenges, we propose a novel approach inspired by facial gender classification techniques in humans: facial chick sexing. This new method does not require expert knowledge and aims to reduce training time while enhancing animal welfare by minimizing chick manipulation. We develop a comprehensive system for training and inference that includes data collection, facial and keypoint detection, facial alignment, and classification. We evaluate our model on two sets of images: Cropped Full Face and Cropped Middle Face, both of which maintain essential facial features of the chick for further analysis. Our experiment demonstrates the promising viability, with a final accuracy of 81.89%, of this approach for future practices in chick sexing by making them more universally applicable.
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