In this paper, we present a new automatic diagnosis method of facial acne vulgaris based on convolutional neural network. This method is proposed to overcome the shortcoming of classification types in previous methods. The core of our method is to extract features of images based on convolutional neural network and achieve classification by classifier. We design a binary classifier of skin-and-...

In this paper, we focus on studying the appearing time of different kinds of cars on the road. This information will enable us to infer the life style of the car owners. The results can further be used to guide marketing towards car owners. Conventionally, this kind of study is carried out by sending out questionnaires, which is limited in scale and diversity. To solve this problem, we propose ...

Autonomous driving has various visual perception tasks such as object detection, 1 motion detection, depth estimation and flow estimation. Multi-task learning (MTL) 2 has been successfully used for jointly estimating some of these tasks. Previous 3 work was focused on utilizing appearance cues. In this paper, we address the gap 4 of incorporating motion cues in a multi-task learning system. We ...

Mental health is an important part of a successful life for person whether elderly, children, or young. Alzheimer’s fatal brain disease that severely damages the human brain, especially in elderly. One way to prevent Alzheimer's by detecting it early. The proposed research employs deep learning methodology using 3D convolutional neural network (3D CNN) has been detect at early stage. model prim...

Qilou (arcade building) is a particular type of Chinese historical architecture combined with western and eastern building elements, which plays significant role in the history modern architecture. However, recognition classification qilou mainly rely on manual inspection, suppressing cultural dissemination protection relics. In this paper, we present new framework that adopts multiple image pr...

Convolutional neural network (CNN) is a method of supervised deep learning. The architectures including AlexNet, VGG16, VGG19, ResNet 50, ResNet101, GoogleNet, Inception-V3, Inception ResNet-V2, and Squeezenet that have 25 to 825 layers. This study aims simplify layers CNN increased accuracy for fundus patches classification. Fundus classify two categories: normal neovascularization. Data used ...

The defect identification of tunnel lining is a task with lot tasks and time-consuming work, currently, it mainly relies on manual operation. This paper takes the ground-penetrating radar image internal defects as research object, chooses popular VGG16, ResNet34 convolutional neural network (CNN) to build automatic recognition model for comparative study, proposes an improved defect-recognition...

With the advancement in pose estimation techniques, human posture detection recently received considerable attention many applications, including ergonomics and healthcare. When using neural network models, overfitting poor performance are prevalent issues. Recently, convolutional networks (CNNs) were successfully used for recognition from images due to their superior multiscale high-level visu...

We develop a method for comparing hierarchical image representations in terms of their ability to explain perceptual sensitivity in humans. Specifically, we utilize Fisher information to establish a model-derived prediction of sensitivity to local perturbations of an image. For a given image, we compute the eigenvectors of the Fisher information matrix with largest and smallest eigenvalues, cor...

Eggplant is a popular vegetable crop. yields can be affected by various diseases. Automatic detection and recognition of diseases an important step toward improving crop yields. In this paper, we used two-stream deep fusion architecture, employing CNN-SVM CNN-Softmax pipelines, along with inference model to infer the disease classes. A dataset 2284 images was sourced from primary (using consume...