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Louis Vuitton Malletier, commonly known as Louis Vuitton (/ luːˈiː vɪˈtɒn / ⓘ, French: [lwi vɥitɔ̃] ⓘ), is a French luxury fashion house and company founded in 1854 by Louis Vuitton. [1] The label's LV monogram appears on most of its products, ranging from luxury bags and leather goods to ready-to-wear, shoes, [4] perfumes, watches, jewellery, accessories, sunglasses and books ...
Yoshida & Co., Ltd. is a Japanese manufacturer based in Tokyo that designs and produces bags and accessories. Founded by Kichizo Yoshida in 1935, the company is best known for its PORTER and LUGGAGE LABEL brands of products.
MCM Worldwide. MCM Worldwide is a luxury fashion brand originally founded in 1976 as the initialism of "Michael Cromer Munich". The brand’s signature logo -printed material, called Cognac Visetos, appears on many of its products. Its brass plate insignia is found on all heritage collection bags and most products; each brass plate is ...
The paper labels that read “sweaters” and “kiddies” were cute touches and made identifying your clothes in suitcases and duffle bags convenient Bags come in various shapes to appeal to all ...
The Row is an American luxury fashion label established by Mary-Kate and Ashley Olsen in 2006 in New York City. The Row produces ready-to-wear clothing, footwear, handbags and accessories. The label has five monobrand stores and is available in 37 countries.
Coach modern-style logo with signature cartouche. Coach's logo found on their products. Coach New York, commonly known as Coach, is an American luxury fashion house headquartered in New York City & specialized in handbags, luggage, and accessories, as well as ready-to-wear. Coach licenses its name and branding to Luxottica for eyewear [4] and ...
Luxury brand Coperni has created a small bag made of nanomaterial silica aerogel — previously used by NASA to collect comet dust.
Multiple instance learning (MIL) falls under the supervised learning framework, where every training instance has a label, either discrete or real valued. MIL deals with problems with incomplete knowledge of labels in training sets. More precisely, in multiple-instance learning, the training set consists of labeled "bags", each of which is a ...
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