Ryoga Nishimura
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Effects of sensory combination on crispness and prediction of sensory evaluation value by Gaussian process regression Open
Crispness contributes to the pleasantness and enjoyment of eating foods and is popular with people of wide ages in many countries. Hence, a quantitative evaluation method for crispness is required for food companies developing new food pro…
EP169/#411 Machine learning method for differential diagnosis and prognosis prediction for early-stage uterine sarcoma using preoperative blood biomarker and age Open
Introduction Preoperative differential diagnosis of clinical stage I uterine sarcoma (US) is essential for surgical intervention. Many studies have been done using CT or MRI imaging for machine learning prediction models but not with blood…
Texture estimation of snack foods using force, vibration, and sound Open
食感推定の精度を向上させるために, 食品押し込み時の荷重と振動と音のデータから特徴量を算出し, 推定に使用する方法を提案した. 8種類のサンプルを磁気式食感センサとマイクを併用した食感計測器で計測すると, 荷重と振動と音の計測結果に違いが見られた. この計測データから算出した特徴量のうち, 荷重, 荷重と振動, 荷重と音, 荷重と振動と音の特徴量を使用してGPRにて推定を行うと, ザクザクは荷重と振動で推定を行なった場合が最も推定精度が高く, サクサク, カリカリ, パリパ…