การตรวจสอบคุณภาพทางกายภาพของข้าวกล้องงอกโดยใช้การประมวลผลภาพ
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งานวิจัยนี้ได้นำเทคโนโลยีการประมวลผลภาพด้วยวิธี Deep Learning และใช้อัลกอริธึม CNN เพื่อสร้างแบบจำลองในการจำแนกเมล็ดข้าวกล้องงอกไรซ์เบอรี่ โดยผู้เชี่ยวชาญและปราชญ์ชาวบ้านได้เลือกข้าวกล้องงอกไรซ์เบอรี่ 500 ตัวอย่าง จากนั้นจึงพัฒนาโปรแกรมและสร้างแบบจำลองโดยใช้ภาพข้าวกล้องงอกไรซ์เบอรี่จำนวน 250 ภาพ และภาพข้าวกล้องไรซ์เบอรี่ที่ไม่ใช่ข้าวกล้องงอกจำนวน 250 ภาพ ผลของการสร้างแบบจำลองแสดงให้เห็นว่าอัลกอริธึม CNN สามารถสร้างแบบจำลองที่มีความแม่นยำสูงถึง 95.17 % และในกระบวนการทดสอบแสดงให้เห็นว่าแบบจำลองที่สร้างขึ้นมีความแม่นยำในการจำแนกรูปภาพของข้าวกล้องโดยผลการทดสอบพบว่ากระบวนการวิจัยและโปรแกรมที่พัฒนาขึ้นมีความแม่นยำในการจำแนกข้าวกล้องงอกได้มากถึง 96% รวมถึงการจำแนกประเภทของข้าวที่ไม่ใช่ข้าวกล้องงอกด้วยความแม่นยำ 84%
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