From:Nexdata Date: 2024-08-15
With the rapid development of AI technology, datasets has become a core factor of improving intelligent system’s performance. The variety and accuracy of datasets determine the learning ability and execution effect of AI models. In the progress of training intelligent system, large amount of datasets from real world are indispensable resources. Collecting and labeling data scientifically can help AI models gain accurate results in real applications, reduce the rate of misjudgment, and improve user experience and system efficiency.
Artificial intelligence (AI) can provide support for retail operations, increasing profits and optimizing business processes. AI services in the retail sector are predicted to increase from $5 billion to above $31 billion by 2028.
Why can retail and e-commerce businesses better serve their customers with the addition of artificial intelligence? This is because AI can aggregate, answer questions and make recommendations for customers across any market or segment. This allows employees to spend less time dealing with day-to-day tasks and more time serving customers better. That's why we provide high-quality training data.
With years of industry experience, we can provide the most up-to-date, accurate, and relevant training data to support our clients. All features needed for each market segment are met, and the required data is collected reasonably and legally.
You can efficiently deploy machine learning in each module with our high-quality training data. Autonomously complete all aspects, including search recommendations to supply chain management to bring a better shopping experience to customers.
With the addition of AI, the e-commerce platform can provide customers with exclusive personalized discount recommendations based on their past purchase history. Thus, it can add value to orders for e-commerce shops and provide a customized experience like live shopping for customers.
The platform can comprehensively understand and judge the products or services that customers need based on all their past searches through AI. And help personalize their predictions for customers to recommend products that match their preferences and tastes.
When users are not sure of the description of a product, such as its name, they cannot search for the product they want. Through the AI image analysis function, users can upload images of the product to the e-commerce store to recommend the best product recommendations that meet their requirements.
The e-commerce platform's AI system predicts and accurately analyzes customers' needs by examining the products in their shopping carts. It effectively provides customers with shopping convenience and significantly increases merchants' sales.
By accurately tracking the number of products in stock, we can keep the supply of popular products. And accurately predict future product demand data to adjust inventory levels and prevent backlogs or out-of-stocks.
Artificial intelligence can significantly satisfy customers who want to experience product fitting before purchase. By uploading personal photos, computer vision can effectively generate the effect of the customer's upper body, as realistic as being in the actual situation.
Datasets recommend
This dataset included 19,968 images of males and 124,842 images of females. The Fashion Items were divided into four parts based on the season (spring, autumn, summer, and winter). In terms of annotation, rectangular bounding boxes were adopted to annotate fashion items. The data can be used for tasks such as fashion item detection, fashion recommendation, and other charges.
The dataset diversity includes multiple scenes, light conditions, ages, shooting angles, and poses. In terms of annotation, we adopted instance segmentation annotations on the human body. Twenty-two landmarks were also annotated for each human body. The dataset can be used for human body instance segmentation and human behavior recognition tasks.
The collecting environments include indoor and outdoor scenes. In this dataset, the image is clear without a watermark, and each image contains at least one trademark. The dataset can be used for scene recognition and trademark classification.
Rectangular bounding boxes were adopted to annotate forms. The data can be used for tasks such as form detection.
With the advancement of data technology, we are heading towards a more intelligent world. The diversity and high-quality annotation of datasets will continue to promote the development of AI system, create greater society benefits in the fields like healthcare, intelligent city, education, etc, and realize the in-depth integration of technology and human well-being.