การประมวลผลภาพสำหรับการจำแนกคุณภาพมะม่วงพันธุ์โชคอนันต์ โดยการจำลองการมองเห็นของมนุษย์ด้วยวิธีการเรียนรู้เชิงลึก
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งานวิจัยนี้ได้นำเทคโนโลยีการประมวลผลภาพด้วยวิธีการเรียนรู้เชิงลึกที่สามารถจำลองการมองเห็นของมนุษย์พัฒนาแบบจำลองสำหรับตรวจสอบและจำแนกคุณภาพมะม่วงพันธุ์โชคอนันต์ โดยดำเนินการเก็บรวบรวมข้อมูลภาพถ่ายมะม่วงพันธุ์โชคอนันต์และเก็บข้อมูลการจำแนกคุณภาพกำหนดระดับคุณภาพออกเป็น 4 ระดับประกอบด้วย คุณภาพระดับเกรด A, คุณภาพระดับเกรด B, คุณภาพระดับเกรด C และคุณภาพระดับเกรด D คือมะม่วงเน่า ผลของการวิจัยแสดงให้เห็นว่าการใช้วิธีการเรียนรู้เชิงลึกด้วยอัลกอริธึมโครงข่ายประสาทเทียมแบบสังวัตนาการ (Convolutional Neural Network: CNN) ในการประมวลผลภาพเพื่อสร้างแบบจำลองแสดงค่าความแม่นยำสูงสุดคือ 99.79% จากนั้นนำแบบจำลองพัฒนาเป็นระบบต้นแบบสำหรับจำแนกคุณภาพมะม่วงพันธุ์โชคอนันต์พบว่าอัตราความสำเร็จในการจำแนกคือ 100%
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