Issues Related to Accuracy and Performance during Classification Process in Sentiment Extraction from Image Description
Puneet Sharma, Sanjay Kumar Malik · 2024
The task of sentiment extraction from visual descriptions encompasses several fields of study, including computer vision, natural language processing, and machine learning. The present work examines the significant concerns pertaining to the precision and efficacy in sentiment categorization while analyzing textual descriptions linked to photographs. The main aim of this study is to establish reliable approaches and models that can accurately perceive and comprehend the emotional tone or mood conveyed in picture descriptions. This study makes a valuable contribution to the field of sentiment analysis in the context of picture descriptions. The findings have the potential to enhance many applications such as social media analysis, e-commerce, and customer feedback analysis. The primary objective of this research is to enhance the proficiency of AI systems in comprehending and appropriately reacting touser emotions and feelings by addressing concerns related to accuracy and performance.