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Fashion Meets Computer Vision

Wen-Huang Cheng, Sijie Song, Chieh-Yun Chen, Shintami Chusnul Hidayati et al. • ACM Computing Surveys (2021)

Fashion is the way we present ourselves to the world and has become one of the world’s largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention from computer vision researchers in recent years. Given the rap...

OPENALEX Open Access DOI: https://doi.org/10.1145/3447239

Three-Dimensional Computer Vision

Olivier D. Faugeras • Cumulative Index of Computer Aided Architectural Design (1993)

This monograph by one of the world's leading vision researchers provides a thorough, mathematically rigorous exposition of a broad and vital area in computer vision: the problems and techniques related to three-dimensional (stereo) vision a...

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Computer vision technology in agricultural automation —A review

Hongkun Tian, Tianhai Wang, Yadong Liu, Xi Qiao et al. • Information Processing in Agriculture (2019)

Computer vision is a field that involves making a machine “see”. This technology uses a camera and computer instead of the human eye to identify, track and measure targets for further image processing. With the development of computer visio...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.inpa.2019.09.006

Computer Vision for Autonomous Vehicles

Joel Janai, Fatma Güney, Aseem Behl, Andreas Geiger • Foundations and Trends® in Computer Graphics and Vision (2020)

Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the fiel...

OPENALEX Open Access DOI: https://doi.org/10.1561/0600000079

Binarized Neural Networks

Itay Hubara, Daniel Soudry, Yaniv, Ran El • arXiv (Cornell University) (2016)

We introduce a method to train Binarized Neural Networks (BNNs) - neural networks with binary weights and activations at run-time and when computing the parameters' gradient at train-time. We conduct two sets of experiments, each based on a...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1602.02505

SPIKING NEURAL NETWORKS

Samanwoy Ghosh‐Dastidar, Hojjat Adeli • International Journal of Neural Systems (2009)

Most current Artificial Neural Network (ANN) models are based on highly simplified brain dynamics. They have been used as powerful computational tools to solve complex pattern recognition, function estimation, and classification problems. A...

OPENALEX DOI: https://doi.org/10.1142/s0129065709002002

Introduction Neural networks in remote sensing

Peter M. Atkinson, Adrian R. L. Tatnall • International Journal of Remote Sensing (1997)

Abstract. Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that ...

OPENALEX DOI: https://doi.org/10.1080/014311697218700

Neural networks for nonlinear programming

Michael Peter Kennedy, Leon Ong Chua • IEEE Transactions on Circuits and Systems (1988)

The dynamics of the modified canonical nonlinear programming circuit are studied and how to guarantee the stability of the network's solution. By considering the total cocontent function, the solution of the canonical nonlinear programming ...

OPENALEX DOI: https://doi.org/10.1109/31.1783