Multi-Scale Receptive Field Detection Network
نویسندگان
چکیده
منابع مشابه
Contour detection model with multi-scale integration based on non-classical receptive field
The broad region outside the classical receptive field (CRF) of a vision neuron, known as the nonclassical receptive field (nCRF), exerts a robust modulatory effect on the responses to visual stimuli presented within the CRF, and plays an important role in visual information processing. One possible role for the nCRF is the extract object contours from disorderly background textures. In this st...
متن کاملA Foreground Inference Network for Video Surveillance Using Multi-View Receptive Field
Foreground (FG) pixel labeling plays a vital role in video surveillance. Recent engineering solutions have attempted to exploit the efficacy of deep learning (DL) models initially targeted for image classification to deal with FG pixel labeling. One major drawback of such strategy is the lacking delineation of visual objects when training samples are limited. To grapple with this issue, we intr...
متن کاملNetwork Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons
Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neur...
متن کاملMulti-Scale Fully Convolutional Network for Fast Face Detection
Image pyramid is a common strategy in detecting objects with different scales in an image. The computation of features at every scale of a finely-sampled image pyramid is the computational bottleneck of many modern face detectors. To deal with this problem, we propose a multi-scale fully convolutional network framework for face detection. In our detector, face models at different scales are tra...
متن کاملContextual Multi-Scale Region Convolutional 3D Network for Activity Detection
Activity detection is a fundamental problem in computer vision. Detecting activities of different temporal scales is particularly challenging. In this paper, we propose the contextual multi-scale region convolutional 3D network (CMSRC3D) for activity detection. To deal with the inherent temporal scale variability of activity instances, the temporal feature pyramid is used to represent activitie...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2942077