Dual Channel with Involution for Long-Tailed Visual Recognition

With the rapid increase of large-scale problems, the distribution of real-world datasets tends to be long-tailed. Existing solutions typically involve re-balancing strategies (i.e., re-sampling and re-weighting). Although they can significantly promote the classifier learning of deep networks, they will unexpectedly impair the representative ability of the learned deep features to a certain extent. Therefore, this paper proposes a dual-channel learning algorithm with involution neural networks (DC-Invo) to take care of representation learning and classifier learning concurrently. In this work, the most important thing is to combine ResNet and involution to obtain higher classification accuracy because of involution’s wider coverage in the spatial dimension. The paper conducted extensive experiments on several benchmark vision tasks including Cifar-LT, Imagenet-LT, and Places-LT, showing that DC-Invo is able to achieve significant performance gained on long-tailed datasets.

长尾理论与大学教材销售渠道创新

长尾理论为大学教材销售渠道的建设和管理指出了方向,即整合传统渠道,提高市场覆盖率;减少流通环节,开辟直接渠道;尝试各种途径,构建新兴渠道。

运用微信搜索开展汽车用品精准引流的探索

应用探索微信搜索精准引流理论,通过理论加实践摸索的方法,研究了汽车用品市场营销领域微信搜索的运用,找出汽车用品在微信搜索内容类别排名的影响因素,得到了汽车用品企业利用微信,长期、持续和免费获客的方法,为汽车用品企业的品牌传播、产品销售及服务跟进持续发力。

安谷水电站长尾水渠与右岸地下水位的影响分析

安谷水电站的长尾水渠布置在大渡河右岸区域,人口、耕地众多,沟渠发达,尾水渠通过优化设计研究取消了右堤的防渗墙。现电站已经运行,为探究尾水渠与右岸区域的地下水位的相互影响,基于饱和-非饱和渗流理论并利用SEEP/W软件对尾水渠右堤进行渗流计算,分析了运行期各剖面的渗流量、渗流场和渗透坡降,同时对右岸地下水位进行长期原型观测,分析其变化趋势。结果表明,尾水渠右堤的渗流量对尾水渠水位的影响可忽略,枯水期靠近尾水渠的右岸地下水位略有影响,且范围有限。

消费者视角的网络零售地域影响因素研究综述

网络零售一直都被认为不受传统零售商圈限制,拥有无限的潜在顾客。然而近年来,越来越多的学者发现,和传统零售一样,网络零售商能够吸引到的实际顾客数量依旧在很大程度上受消费者所在地域位置的影响。有鉴于此,本文聚焦于消费者视角,基于消费者渠道迁徙理论、社会互动理论和长尾理论,综述了目前国内外关于网络零售地域影响因素的研究成果,并相应地总结了现有研究针对相关影响因素给网络零售企业提出的营销策略建议,最后展望了该领域的未来研究方向,以期为相关研究和管理实践提供借鉴。