Deep Multi-Scale Convolutional Neural Network for …

What Have We Learned From Deep Representations for …

what these powerful models actually have learned. In this paper we shed light on deep spatiotemporal net-works by visualizing what excites the learned models us-ing activation maximization by backpropagating on the in-put. We are the first to visualize the hierarchical features

  What, Have, Learned, What we have learned, Have learned

Finding Tiny Faces in the Wild With Generative Adversarial ...

faces, which are unfriendly for the face classifier. Toward-s this end, we design a refinement sub-network to recover some detailed information. In the discriminator network, the basic GAN [17, 12, 8] is trained to distinguish the real and fake high resolution images. To classify faces or non-

  Faces

Squeeze-and-Excitation Networks - openaccess.thecvf.com

Squeeze-and-Excitation Networks Jie Hu1∗ Li Shen2∗ Gang Sun1 hujie@momenta.ai lishen@robots.ox.ac.uk sungang@momenta.ai 1 Momenta 2 Department of Engineering Science, University of Oxford Abstract Convolutional neural networks are built upon the con-

  Network, Excitation, Squeeze and excitation networks, Squeeze

RegularFace: Deep Face Recognition via Exclusive ...

RegularFace: Deep Face Recognition via Exclusive Regularization Kai Zhao Jingyi Xu Ming-Ming Cheng ∗ TKLNDST, CS, Nankai University kaiz.xyz@gmail.com cmm@nankai.edu.cn

  Zhao

Protecting World Leaders Against Deep Fakes

Protecting World Leaders Against Deep Fakes Shruti Agarwal and Hany Farid University of California, Berkeley Berkeley CA, USA {shrutiagarwal, hfarid}@berkeley.edu

Auto-DeepLab: Hierarchical Neural Architecture Search for ...

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation Chenxi Liu1∗, Liang-Chieh Chen 2, Florian Schroff2, Hartwig Adam2, Wei Hua2, Alan Yuille1, Li Fei-Fei3 1Johns Hopkins University 2Google 3Stanford University Abstract Recently, NeuralArchitectureSearch(NAS)hassuccess-

PointNet: Deep Learning on Point Sets ... - CVF Open Access

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Charles R. Qi* Hao Su* Kaichun Mo Leonidas J. Guibas Stanford University

  Open, Learning, Points, Deep, Sets, Pointnet, Deep learning on point sets

Frustum PointNets for 3D Object Detection From RGB-D Data

Frustum PointNets for 3D Object Detection from RGB-D Data Charles R. Qi1∗ Wei Liu2 Chenxia Wu2 Hao Su3 Leonidas J. Guibas1 1Stanford University 2Nuro, Inc. 3UC San Diego Abstract In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.

Class-Balanced Loss Based on Effective Number of Samples

and large-scale datasets including ImageNet and iNatural-ist. Our results show that when trained with the proposed class-balanced loss, the network is able to achieve signifi-cant performance gains on long-tailed datasets. 1. Introduction The recent success of deep Convolutional Neural Net-works (CNNs) for visual recognition [26, 37, 38, 16] owes

  Scale, Visual, Recognition, Visual recognition

ESRGAN: Enhanced Super-Resolution Generative Adversarial ...

ESRGAN: EnhancedSuper-Resolution Generative Adversarial Networks Xintao Wang 1, Ke Yu , Shixiang Wu2, Jinjin Gu3, Yihao Liu4, Chao Dong 2, Yu Qiao , and Chen Change Loy5 1 CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong 2 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences 3 The Chinese University of Hong Kong, …

  Network, Adversarial, Generative, Generative adversarial, Generative adversarial networks

SPI / I²C & MIPI I3C LSM6DSO

• Embedded temperature sensor ... The LSM6DSO has a full-scale acceleration range of ±2/±4/±8/±16 g and an angular ... The LSM6DSO is available in a small plastic land grid array (LGA) package of 2.5 x 3.0 x 0.83 mm to address ultra-compact solutions. LSM6DSO Overview

  Scale, Small, Embedded

UNIT-I - OVERVIEW OF EMBEDDED SYSTEMS Embedded …

Small Scale Embedded Systems These types of embedded systems are designed with a single 8 or 16-bit microcontroller, that may even be activated by a battery. For developing embedded software for small scale embedded systems, the main programming tools are an editor, assembler, cross assembler and integrated development environment (IDE).

  Scale, Small, Embedded, Small scale embedded

EMBEDDED SYSTEM BASICS AND APPLICATION

SMALL SCALE EMBEDDED SYSTEM • Single 8 bit or 16bit Microcontroller. • Little hardware and software complexity. • They May even be battery operated. • Usually “C”is used for developing these system. • The need to limit power dissipation when system is running continuously. Programming tools: Editor, Assembler and Cross Assembler

  Scale, Small, Embedded, Small scale embedded

A Study of Co-Teaching Identifying Effective ...

A rating scale, interview, and classroom observation of the participants were the data sources. The qualitative rating scale survey was used to glean practical and relevant information instead of a quantitative rating scale due to the small sample size (Jensen, 2010; Kelley, Clark, Brown, & …

  Scale, Small

DynamicFusion: Reconstruction and Tracking of Non-rigid ...

researchers have extended ICP to enable small non-rigid deformations, e.g., [1,2]. Practical advancements to pair-wise 3D shape and scan alignment over larger deformations make use of reduced deformable model parametrisations [14,4]. In particular, embedded deformation graphs [25] use a sparsely sampled set of transformation basis func-

  Small, Tracking, Reconstruction, Embedded, Dynamicfusion, Reconstruction and tracking of

3-Axis, ±2 Data Sheet ADXL345 - Analog Devices

scale factor in all g ranges ) Embedded memory management system with FIFO technology minimizes host processor load Single tap/double tap detection Activity/inactivity monitoring Free-fall detection Supply voltage range: 2.0 V to 3.6 V I/O voltage range: 1.7 V to V S SPI (3- and 4-wire) and I 2C digital interfaces

  Devices, Scale, Analog devices, Analog, Embedded

How the SOAFEE Architecture Brings A Cloud-Native …

The historical problem of developing code for embedded systems like those in the automotive domain has been ... we think of the large-scale applications that are running in the cloud. The infrastructure market and Cloud Service Providers (CSP’s) ... crun Small footprint lightweight runtime implemented in C

  Scale, Small, Embedded