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Jurandy Almeida
Affiliation
Department of Computing (DComp-So), Federal University of São Carlos (UFSCar), Sorocaba, Brazil
Topic
Convolutional Neural Network,Data Augmentation,Deep Learning,Neural Network,Convolutional Network,Inference Time,Self-supervised Learning,Transfer Learning,1D Convolutional Layers,Action Recognition,Agricultural Fields,Attention Mechanism,Audio Files,Audio Recordings,Augmentation Approach,Automatic Speech Recognition System,Benchmark Results,Binary Classification,Body Movements,Camera Movement,Channel Selection,Class Boundaries,Classification Of Diseases,Cloud Computing,Complex Models,Compressed Domain,Compressed Format,Computational Cost,Computer Vision,Convolutional Layers,Crop Diseases,Crop Fields,Crop Yield,Cross-entropy Loss Function,Data Augmentation Methods,Data Augmentation Techniques,Deep Learning Models,Discrete Cosine Transform,Domain Adaptation,Domain Shift,Domain Shift Problem,Edge Computing,Edge Devices,Edge Server,F1 Score,False Negative,Field Of Computer Vision,Field Of Production,Frame Rate,Frequency Domain,
Biography
Jurandy Almeida was born in Sorocaba, Brazil, on May 20, 1983. He
received the B.Sc. degree in computer science from São Paulo State University (UNESP), Bauru, Brazil, in 2004,
and the M.Sc. and Ph.D. degrees in computer science from University of Campinas (UNICAMP), Campinas, Brazil, in 2007
and 2011, respectively.
From 2011 to 2013, he was an Associate Researcher at the Institute of Computing, UNICAMP. Since 2013, he has been an Assistant Professor at the Institute of Science and Technology, Federal University of São Paulo (UNIFESP), São José dos Campos, Brazil. He has developed research on databases, image processing, machine learning, and computer vision in applications of visual information retrieval.
From 2011 to 2013, he was an Associate Researcher at the Institute of Computing, UNICAMP. Since 2013, he has been an Assistant Professor at the Institute of Science and Technology, Federal University of São Paulo (UNIFESP), São José dos Campos, Brazil. He has developed research on databases, image processing, machine learning, and computer vision in applications of visual information retrieval.