1 citations · 2 across the 4 of their papers we have counts for
5 papers
Enhanced Sentiment Interpretation via a Lexicon-Fuzzy-Transformer Framework
Shayan Rokhva, Mousa Alizadeh, Maryam Abdollahi Shamami
Accurately detecting sentiment polarity and intensity in product reviews and social media posts remains challenging due to informal and domain-specific language. To address this, w…
Artificial Intelligence in the Food Industry: Food Waste Estimation based on Computer Vision, a Brief Case Study in a University Dining Hall
Shayan Rokhva, Babak Teimourpour
Quantifying post-consumer food waste in institutional dining settings is essential for supporting data-driven sustainability strategies. This study presents a cost-effective comput…
Enhanced Sentiment Analysis of Iranian Restaurant Reviews Utilizing Sentiment Intensity Analyzer & Fuzzy Logic
Shayan Rokhva, Babak Teimourpour, Romina Babaei
This research presents an advanced sentiment analysis framework studied on Iranian restaurant reviews, combining fuzzy logic with conventional sentiment analysis techniques to asse…
A Novel Method for Accurate & Real-time Food Classification: The Synergistic Integration of EfficientNetB7, CBAM, Transfer Learning, and Data Augmentation
Shayan Rokhva, Babak Teimourpour
Integrating artificial intelligence into modern society is profoundly transformative, significantly enhancing productivity by streamlining various daily tasks. AI-driven recognitio…
Computer Vision in the Food Industry: Accurate, Real-time, and Automatic Food Recognition with Pretrained MobileNetV2
Shayan Rokhva, Babak Teimourpour, Amir Hossein Soltani
In contemporary society, the application of artificial intelligence for automatic food recognition offers substantial potential for nutrition tracking, reducing food waste, and enh…