Fast auto-clean CNN model for online prediction of food materials

Image Augmentation-Based Food Recognition with Convolutional Neural Networks

“…At present, food-ingredient suppliers detected abundant categories of food ingredients and labeled them properly with the human visual system. This process is very tiring, uninteresting, and expensive [Chen, Xu, Xiao et al (2017)]. Therefore, it becomes urgent to construct a food-ingredient recognition system, which can intelligently recognize food-ingredient images and label correct food categories.…”

“…Recently, image recognition implements great growth in many fields [Li, Qin, Xiang et al (2018); Pouyanfar and Chen (2016); Chen, Zhu, Lin et al (2013); Liu, Wang, Liu et al (2017)], such as remote sensing, digital telecommunications, medical imaging, and so on. A variety of work have shown that deep learning and machine learning technologies can be exploited to retrieve food images intelligently [Chen, Xu, Xiao et al (2017); Pan, Pouyanfar, Chen et al (2017); Yanai and Kawano (2015); Joutou and Yanai (2009)]. While most food recognition methods concentrate on diet [Joutou and Yanai (2009); Hoashi, Joutou and Yanai (2010); Kagaya, Aizawa and Ogawa (2014)], and food datasets are mainly made up of food meal images.…”

“…Nowadays, few food-ingredient datasets (as shown in Fig. 2) are obtainable, and thus, the multi-category detection of food ingredients is limited in existing literature [Chen, Xu, Xiao et al (2017); Pan, Pouyanfar, Chen et al (2017)] and the size of obtained foodingredient images is commonly small scale or medium. To effectively classify small and medium food-ingredient datasets, this study presents an image augmentation-based food recognition architecture utilizing deep learning.…”

Resource allocation and interference management for multi-layer wireless networks in heterogeneous cognitive networks

“…Cognitive radio network, small cell network, wireless local area network, WiMAX, and LTE network will promote the next generation network communication technology to achieve greater development. In addition, tablet computers, smartphones, and so on have gradually become an indispensable office and communication tools in people's daily life [1][2][3]. With the popularity of these new handheld devices, data-intensive applications such as video conversation, online games, online music, and video streaming are becoming more and more popular, and the era of mobile Internet has come.…”

“…. A represents the allocation indicator matrix of the resource block, which is defined as A = [A(1) ⋯A (i) ⋯A (M) ] and A ðiÞ ¼ ½a ðiÞ value can only be 0 or 1, indicating whether the kth resource block is allocated to the nth user in the ith flying cell.…”