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Computer Vision

George C. Stockman, Linda G. Shapiro (2001)

From the Publisher: Computer Vision presents the necessary theory and techniques for students and practitioners who will work in fields where significant information must be extracted automatically from images. It will be a useful resource...

OPENALEX

ALGORITMO PARA O RECONHECIMENTO DE CARACTERES MANUSCRITOS

Rafael Arthur Rocha Miranda, Francisco Assis da Silva, Mário Augusto Pazoti, Almir Olivette Artero et al. • Colloquium Exactarum (2013)

The handwritten character recognition in digital images is an important and challenging area of study in Computer Vision, with several possibilities for applications to facilitate the daily work of the people. This paper presents an alg...

DOAJ Open Access (DOAJ) DOI: 10.5747/ce.2013.v05.n2.e062

Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks

Marco Antonio Contreras-Cruz, Juan Pablo Ramirez-Paredes, Uriel Haile Hernandez-Belmonte, Victor Ayala-Ramirez • Sensors (2019)

One of the essential abilities in animals is to detect novelties within their environment. From the computational point of view, novelty detection consists of finding data that are different in some aspect to the known data. In robotics, re...

DOAJ Open Access (DOAJ) DOI: 10.3390/s19132965

A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence

Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar et al. • Technologies (2023)

Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies11020055

A Dual-Segmentation Framework for the Automatic Detection and Size Estimation of Shrimp

Malik Muhammad Waqar, Hassan Ali, Heng Zhou, Heba G. Mohamed et al. • Sensors (2025)

In shrimp farming, determining the physical traits of shrimp is vital for assessing their health and growth. One of the critical traits is their size, as it serves as a key indicator of growth rates, biomass, and effective feed management. ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s25185830

Deep Learning in Microscopy Image Analysis: A Survey

Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems (2017)

Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...

OPENALEX DOI: https://doi.org/10.1109/tnnls.2017.2766168

Deep Learning

• De Gruyter eBooks (2020)

This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...

OPENALEX DOI: https://doi.org/10.1515/9783110670905

A Review on Conventional Machine Learning vs Deep Learning

Nitin Kumar Chauhan, Krishna Pal Singh • International Conference on Computing, Power and Communication Technologies (GUCON) (2018)

In now days, deep learning has become a prominent and emerging research area in computer vision applications. Deep learning permits the multiple layers models for computation to learn representations of data by processing in their original ...

OPENALEX DOI: https://doi.org/10.1109/gucon.2018.8675097

A State-of-the-Art Survey on Deep Learning Theory and Architectures

Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics (2019)

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...

OPENALEX cc-by DOI: https://doi.org/10.3390/electronics8030292

Review: Deep Learning on 3D Point Clouds

Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing (2020)

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...

OPENALEX cc-by DOI: https://doi.org/10.3390/rs12111729

Deep learning-enabled medical computer vision

Andre Esteva, Katherine Chou, Serena Y. Yeung, Nikhil Naik et al. • npj Digital Medicine (2021)

A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields-including medicine-to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in th...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41746-020-00376-2 PMC: 7794558

A Survey of Deep Learning-Based Object Detection

Licheng Jiao, Fan Zhang, Fang Liu, Shuyuan Yang et al. • IEEE Access (2019)

Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in people’s life, such as monitoring security, autonomous driving and so on, with the purpose of locating instances of ...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2019.2939201

Deep learning and computer vision will transform entomology

Toke T. Høye, Johanna Ärje, Kim Bjerge, Oskar Liset Pryds Hansen et al. • Proceedings of the National Academy of Sciences (2021)

ABSTRACT Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phe...

OPENALEX cc-by DOI: https://doi.org/10.1073/pnas.2002545117 PMC: 7812775

Deep Learning: An Update for Radiologists

Phillip M. Cheng, Emmanuel Montagnon, Rikiya Yamashita, Ian Pan et al. • Radiographics (2021)

Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the...

OPENALEX cc-by DOI: https://doi.org/10.1148/rg.2021200210

Deep Learning in Computer Vision

M. Hassaballah, Ali Ismail Awad • CRC Press eBooks (2020)

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained u ......

OPENALEX DOI: https://doi.org/10.1201/9781351003827