In the world of e-commerce, where clothes are flying off virtual shelves like hotcakes, it’s crucial to classify apparel based on its collar design. However, traditional image processing methods struggle to handle the increasingly complex image backgrounds. That’s where the EMRes-50 classification algorithm swoops in to save us! This algorithm combines the ECA-ResNet50 model with the MC-Loss loss function method to achieve accurate collar image classification. The algorithm was put to the test using two datasets: Coller-6 and DeepFashion-6. With Coller-6, it achieved a classification accuracy of 73.6%. But wait, there’s more! When tested on DeepFashion-6, the accuracy skyrocketed to 86.09%! These exciting experimental results indicate that the improved model outperforms existing CNN models in feature extraction and fine-grained collar classification. So if you’re curious about the future of clothing product image classification, check out the underlying research!
With the rapid development of apparel e-commerce, the variety of apparel is increasing, and it becomes more and more important to classify the apparel according to its collar design. Traditional image processing methods have been difficult to cope with the increasingly complex image backgrounds. To solve this problem, an EMRes-50 classification algorithm is proposed to solve the problem of garment collar image classification, which is designed based on the ECA-ResNet50 model combined with the MC-Loss loss function method. Applying the improved algorithm to the Coller-6 dataset, and the classification accuracy obtained was 73.6%. To further verify the effectiveness of the algorithm, it was applied to the DeepFashion-6 dataset, and the classification accuracy obtained was 86.09%. The experimental results show that the improved model has higher accuracy than the existing CNN model, and the model has better feature extraction ability, which is helpful to solve the problem of the difficulty of fine-grained collar classification and promote the further development of clothing product image classification.
Dr. David Lowemann, M.Sc, Ph.D., is a co-founder of the Institute for the Future of Human Potential, where he leads the charge in pioneering Self-Enhancement Science for the Success of Society. With a keen interest in exploring the untapped potential of the human mind, Dr. Lowemann has dedicated his career to pushing the boundaries of human capabilities and understanding.
Armed with a Master of Science degree and a Ph.D. in his field, Dr. Lowemann has consistently been at the forefront of research and innovation, delving into ways to optimize human performance, cognition, and overall well-being. His work at the Institute revolves around a profound commitment to harnessing cutting-edge science and technology to help individuals lead more fulfilling and intelligent lives.
Dr. Lowemann’s influence extends to the educational platform BetterSmarter.me, where he shares his insights, findings, and personal development strategies with a broader audience. His ongoing mission is shaping the way we perceive and leverage the vast capacities of the human mind, offering invaluable contributions to society’s overall success and collective well-being.