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As obras disponibilizadas nesta Biblioteca Digital foram publicadas sob expressa autorização dos respectivos autores, em conformidade com a Lei 9610/98.
A consulta aos textos, permitida por seus respectivos autores, é livre, bem como a impressão de trechos ou de um exemplar completo exclusivamente para uso próprio. Não são permitidas a impressão e a reprodução de obras completas com qualquer outra finalidade que não o uso próprio de quem imprime.
A reprodução de pequenos trechos, na forma de citações em trabalhos de terceiros que não o próprio autor do texto consultado,é permitida, na medida justificada para a compreeensão da citação e mediante a informação, junto à citação, do nome do autor do texto original, bem como da fonte da pesquisa.
A violação de direitos autorais é passível de sanções civis e penais.
Coleção Digital
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Feitosa, Raul Queiroz
1956 -
Professor Assistente
Departamento de Engenharia Elétrica
PUC-Rio
Materiais Relacionados:
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- OPEN SET
- OS SUPPORT
- VISUAL FOUNDATION MODELS
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- VLM - THEORY
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- DATA FUSION - THEORY
- VISION LANGUAGE MODEL
- VISION TRANSFORMERS 2023
- SELF SUPERVISED LEARNING - HANDS-ON
- TRANSFORMERS HANDS-ON
- VISION TRANSFORMERS
- DOMAIN ADAPTATION HANDS-ON
- SELF SUPERVISED LEARNING - THEORY
- AUTOML - HANDS ON
- AUTOML - THEORY
- SPATIOTEMPORAL FORECASTING
- UNCERTAINTY IN DEEP LEARNING - HANDS ON
- UNCERTAINTY IN DEEP LEARNING - THEORY
- VISION TRANSFORMERS
- VISION TRANSFORMERS
- SELF ATTENTION - HANDS ON
- SELF ATTENTION
- AUTOENCODERS
- AUTOENCODERS - HANDS ON
- UNSUPERVISED LEARNING
- GANS HANDS-ON
- UNSUPERVISED LEANING- HANDS ON
- GANS
- MASK R-CNN HANDS-ON
- MASK R-CNN
- RNN HANDS ON
- INTERCONNECTION STRUCTURES 2
- YOLO
- AULA 04 - SEMANTIC SEGMENTATION - PART 1
- AULA 05 - SEMANTIC SEGMENTATION - PART 2
- AULA 06 - RECURRENT NEURAL NETWORKS
- HOMEWORK 2 - SEMANTIC SEGMENTATION
- SEMANTIC SEGMENTATION HANDS-ON
- SEMANTIC SEGMENTATION HANDS-ON
- AULA 03 - CNN ARCHITECTURES
- AULA 03 - GENERALIZATION
- AULA 03 - OPTIMIZATION
- AULA 03 - OPTIMIZATION HANDS ON
- AULA 02 - BACKPROPAGATION
- AULA 02 - CNN + CNN TRAINING
- LECTURE 01 - INTRODUCTION
- AULA 26 - RISC
- AULA 23 - PARALLEL COMPUTERS 2
- AULA 25- MICROARCHITECTURE
- AULA 12 - AUTOML - HANDS ON
- AULA 24 - MULTICORE
- AULA 12 - AUTOML
- AULA 20 - PROCESSOR ORGANIZATION 2
- AULA 21 - SUPERSCALAR PROCESSORS
- AULA 22 - PARALLEL COMPUTERS 1
- AULA 19 - PROCESSOR ORGANIZATION 1
- AULA 11 - METALEARNING 1
- AULA 11 - METALEARNING 1 DEMO
- AULA 11 - METALEARNING 2
- AULA 11 - METALEARNING 2 DEMO
- AULA 10 - UNSUPERVISED LEARNING 2
- AULA 10 - UNSUPERVISED LEARNING 2 - HANDS ON
- AULA 09 - CHANGE DETECTION
- AULA 09 - CHANGE DETECTION - HANDS-ON
- AULA 17 - OPERATING SYSTEM SUPPORT 2
- AULA 08 - UNSUPERVISED LEARNING 1
- AULA 08 - UNSUPERVISED LEARNING 1 - HANDS ON
- AULA 16 - OPERATING SYSTEM SUPPORT 1
- AULA 07 - DPT
- AULA 07 - SWINUNET
- AULA 07 - VISION TRANSFORMERS
- AULA 07 - VISION TRANSFORMERS
- AULA 14 - INPUT/OUTPUT 2
- AULA 12 - EXTERNAL MEMORY 2
- AULA 13- INPUT/OUPUT 1
- AULA 06 - DATA FUSION
- AULA 06 - DATA FUSION - HANDS ON
- AULA 11 - SECONDARY MEMORY 1
- AULA 05 - SELF-ATTENTION
- AULA 05 - SELF-ATTENTION - HANDS-ON
- AULA 10 - INTERCONNECTION STRUCTURES 2
- AULA 09 - INTERCONNECTION STRUCTURES 1
- AULA 09 - INTERNAL MEMORY 2
- AULA 04 - DOMAIN ADAPTATION - HANDS ON
- AULA 08 - INTERNAL MEMORY 1
- DOMAIN ADAPTATION - THEORY
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- AULA 05 - CACHE 1
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- AULA 02 - BIAS AND FAIRNESS
- AULA 02 - BIAS AND FAIRNESS - HANDS ON
- AULA 04 - DESIGNING FOR PERFORMANCE
- AULA 03 - CODIGOS 1
- AULA 02 - COMPUTER PERFORMANCE 2
- AULA 01 - UNCERTAINTY
- AULA 01 - UNCERTAINTY - HANDS ON
- AULA 01 - DESIGNING FOR PERFORMANCE 1
- AULA 15 - UNSUPERVISED LEARNING
- AULA 15 - UNSUPERVISED LEARNING - PRACTICE
- AULA 16 - AUTOENCODERS
- AULA 16 - AUTOENCODERS - PRACTICE
- AULA 14 - SIMILARITY LEARNING
- AULA 22 - SUPERSCALAR PROCESSORS 2
- AULA 13 - GANS
- AULA 13 - GANS - PRACTICE
- AULA 20 - OS SUPPORT 4
- AULA 20 - PROCESSOR ORGANIZATION 2
- AULA 21 - SUPERSCALAR PROCESSORS
- AULA 11 - OBJECT DETECTION
- AULA 11 - OBJECT DETECTION - PRACTICE
- AULA 19 - PROCESSOR ORGANIZATION 1
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- AULA 12 - INSTANCE SEGMENTATION - MASK R-CNN - PRACTICE
- AULA 18 - OS SUPPORT 3
- AULA 17 - OS SUPPORT 2
- AULA 16 - INPUTOUTPUT 4
- AULA 16 - OS SUPPORT 1
- AULA 15 - INPUTOUTPUT 3
- AULA 14 - INPUTOUTPUT 2
- AULA 10 - RECURRENT NEURAL NETWORKS
- AULA 10 - RECURRENT NEURAL NETWORKS - PRACTICE
- AULA 10 - RECURRENT NEURAL NETWORKS - PRACTICE
- AULA 11 - SECONDARY MEMORY 1
- AULA 12 - SECONDARY MEMORY 2
- AULA 13 - INPUTOUTPUT 1
- AULA 13 - SECONDARY MEMORY 3
- AULA 09 - SEMANTIC SEGMENTATION - PRACTICE
- AULA 09 - SEMANTIC SEGMENTATION 2
- AULA 10 - PROBLEMS
- AULA 09 - INTERCONNECTIONS STRUCTURES 2
- AULA 08 - INTERCONNECTION STRUCTURES 1
- AULA 08 - INTERNAL MEMORY 2
- AULA 08 - SEMANTIC SEGMENTATION - PART 1
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- AULA 06 - CACHE 2
- AULA 07 - INTERNAL MEMORY 1
- AULA 04 - CNN TRAINING - PART 2
- AULA 05 - CACHE - PARTE 1
- AULA 05 - GENERALIZATION
- AULA 06 - OPTIMIZATION
- AULA 07 - CNN ARQUITETURES
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- AULA 02 - CNN
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- BACKPROPAGATION - HANDS ON
- CÓDIGOS (EXERCICIOS)
- AULA 02 - COMPUTER PERFORMANCE 1
- AULA 01 - INTRODUCTION TO DEEP LEARNING
- AULA 01 - INTRODUCTION TO DEEP LEARNING - HANDS ON
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- AULA 21 - PIPELINING 2
- AULA 21 - SUPERSCALAR 1
- AULA 20 - PIPELINING 1
- AULA 19 - OPERATING SYSTEM SUPPORT 3
- AULA 18 - OPERATING SYSTEM SUPPORT 2
- AULA 08 - PRODES PROJECT
- AULA 08 - PRODES PROJECT - PRACTICE
- AULA 15/16 - INPUT/OUTPUT 2
- AULA 17 - OPERATING SYSTEM SUPPORT 1
- AULA 15 - EXTERNAL MEMORY 3
- AULA 15 - INPUTOUTPUT 1
- AULA 16 - INPUT/OUTPUT 2
- AULA 08 - CHANGE DETECTION IN THE ERA OF DEEP LEARNING
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- AULA 13 - SECONDARY MEMORY 1
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- PROJECT PROPOSAL - DOMAIN ADAPTATION FOR DEFORESTATION DETECTION USING SEMI-SUPERVISED GANS
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- AULA 20 - SUPERSCALAR 2
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- AULA 19 - SUPERSCALAR 1
- AULA 18 - PIPELINE 2
- AULA 19 - OS SUPPORT 4
- AULA 18 - SUPORTE AO SO 3
- AULA 16 - SUPORTE SO 2
- AULA 17 - PIPELINING 1
- AULA 09 - GANS
- AULA 09 - GANS PRACTICE
- AULA 10 - AUTOENCODERS
- AULA 10 - AUTOENCODERS - PRACTICE
- AULA 10 - AUTOENCODERS - PRACTICE
- AULA 15 - SUPORTE AO SO 1
- AULA 13 - ENTRADA SAIDA 3
- AULA 08 - OBJECT DETECTION 2
- AULA 08 - OBJECT DETECTION 2 - PRACTICE
- AULA 11 - ENTRADA/SAIDA 1
- AULA 12 - ENTRADA/SAIDA 2
- PROJECT PROPOSAL - DEFORESTATION FROM LONG IMAGE SEQUENCES
- AULA 08 - ESTRUTURAS DE INTERCONEXÃO 1
- PROJEC PROPOSAL - NEURAL ARCHITECTURE SEARCH
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- AULA 10 - MEMÓRIA SECUNDÁRIA 1
- AULA 07 - OBJECT DETECTION 1
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- HOMEWORK 3 - LSTM
- AULA 06 - RECURRENT NEURAL NETWORKS
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- AULA 09 - ESTRUTURAS DE INTERCONEXÃO 2
- AULA 05 - SEMANTIC SEGMENTATION 2
- AULA 05 - SEMANTIC SEGMENTATION 2
- AULA 05 -SEMANTIC SEGMENTATION PRACTICE
- HOMEWORK 2 - U-NET
- AULA 08 - MEMORIA INTERNA
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- AULA 07 - CACHE 2
- AULA 04 - CNN ARCHITECTURES 2
- AULA 04 - SEMANTIC SEGMENTATION 1
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- AULA 06 - CACHE MEMORY 1
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- AULA 03 - OPTIMIZATION PRACTICE
- AULA 04 - PERFORMANCE 3
- AULA 04- CÓDIGOS 1
- AULA 02 - BACKPROPAGATION
- AULA 02 - CNN
- AULA 02 - CNN TRAINING
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- AULA 01 - INTRODUCTION
- LECTURE 14 - FINAL PROJECT PRESENTATIONS
- AULA 26 - MULTICORE COMPUTERS
- AULA 23 - SUPERSCALAR COMPUTERS 2C
- AULA 25 - PARALLEL PROCESSING 2 - EXERCISE 4
- AULA 25 - PARALLEL PROCESSING 2
- AULA 24 - PARALLEL PROCESSING 1
- LECTURE 13 - OPEN SET LEARNING - PRACTICE
- AULA 22 - SUPERESCALAR COMPUTERS 1
- AULA 23 - SUPERESCALAR COMPUTERS 2
- LECTURE 13 - OPEN SET LEARNING - THEORY
- LECTURE 12 - UNSUPERVISED LEARNING - PRACTICE 2
- LECTURE 12 - UNSUPERVISED LEARNING - THEORY 2
- AULA 21 - OS SUPPORT 4
- AULA 21 - PIPELINING 1
- LECTURE 11 - UNSUPERVISED LEARNING - PRACTICE 1
- LECTURE 11 - UNSUPERVISED LEARNING - THEORY 1
- AULA 19 - OS SUPPORT 2
- AULA 20 - OS SUPPORT 3 2ND TRY
- AULA 18B - OS SUPPORT 1 2ND TRY
- LECTURE 10 - ATTENTION - PRACTICE
- LECTURE 10 - ATTENTION - THEORY 1
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- AULA 17 - INPUT/OUTPUT 2
- AULA 18A - INPUT/OUTPUT 3
- AULA 18B - OS SUPPORT 1
- LECTURE 08 - OBJECT DETECTION - PRACTICE 2
- LECTURE 08 - OBJECT DETECTION - PRACTICE 2
- LECTURE 09 - MULTI OBJECT TRACKING - PRACTICE
- LECTURE 09 - MULTI OBJECT TRACKING - PRACTICE 2
- LECTURE 09 - MULTI OBJECT TRACKING - THEORY
- LECTURE 08 - OBJECT DETECTION - PRACTICE
- LECTURE 08 - OBJECT DETECTION - THEORY
- AULA 16 - INPUT/OUTPUT 1
- AULA 03 - COMPUTER PERFORMANCE 2
- AULA 14 - SECONDARY MEMORY 2
- LECTURE 07 - ANTI-SPOOFING - PRACTICE 2
- LECTURE 07 - ANTI-SPOOFING - PRACTICE 1
- LECTURE 07 - ANTI-SPOOFING - THEORY
- AULA 12 - INTERCONNECTION STRUCTURES 3
- AULA 11 - INTERCONNECTION STRUCTURES 2
- LECTURE 06 - SIMILARITY LEARNING - PRACTICE 2
- LECTURE 06 - SIMILARITY LEARNING - THEORY 2
- AULA -08 - CACHE 3
- AULA -09 - INTERNAL MEMORY
- AULA 10 - INTERCONNECTION STRUCTURES 1
- LECTURE 09 - INTERNAL MEMORY
- LECTURE 05 - SIMILARITY LEARNING - THEORY 1
- LECTURE 05- SIMILARITY LEARNING - PRACTICE
- LECTURE 04 - DATA FUSION - THEORY
- LECTURE 04 - DATA FUSION - PRACTICE
- AULA 07: CACHE 2
- LECTURE 03 - DOMAIN ADAPTATION - PRACTICE
- LECTURE 03 - DOMAIN ADATATION - THEORY
- AULA 06 - CACHE 1
- AULA 05 - CÓDIGOS 2
- AULA 04A - DESIGNING FOR PERFORMANCE 3
- AULA 04B- CÓDIGOS 1
- LECTURE 02 - DOMAIN ADAPTATION - DENNIS WITTICH
- AULA 03 - DESIGNING FOR PERFORMANCE 2
- AULA 01 - INTRODUÇÃO
- AULA 02 - DESIGNING FOR PERFORMANCE 1
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- LECTURE 09 - MULTI OBJECT TRACKING - PRACTICE
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- AULA 03 - GENERALIZATION
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- AULA 03 - OPTIMIZATION
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- AULA 02 - BACKPROPAGATION
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- AULA 02 - CNN + CNN TRAINING
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- AULA 12 - AUTOML - HANDS ON
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- AULA 24 - MULTICORE
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- AULA 20 - PROCESSOR ORGANIZATION 2
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- AULA 21 - SUPERSCALAR PROCESSORS
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- AULA 22 - PARALLEL COMPUTERS 1
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- AULA 19 - PROCESSOR ORGANIZATION 1
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- AULA 11 - METALEARNING 1
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- AULA 11 - METALEARNING 1 DEMO
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- AULA 11 - METALEARNING 2
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- AULA 11 - METALEARNING 2 DEMO
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- AULA 10 - UNSUPERVISED LEARNING 2
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- AULA 10 - UNSUPERVISED LEARNING 2 - HANDS ON
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- AULA 09 - CHANGE DETECTION
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- AULA 09 - CHANGE DETECTION - HANDS-ON
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- AULA 17 - OPERATING SYSTEM SUPPORT 2
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- AULA 08 - UNSUPERVISED LEARNING 1
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- AULA 08 - UNSUPERVISED LEARNING 1 - HANDS ON
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- AULA 16 - OPERATING SYSTEM SUPPORT 1
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- AULA 07 - DPT
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- AULA 07 - SWINUNET
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- AULA 07 - VISION TRANSFORMERS
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- AULA 14 - INPUT/OUTPUT 2
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- AULA 12 - EXTERNAL MEMORY 2
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- AULA 13- INPUT/OUPUT 1
06/10/2022
- AULA 06 - DATA FUSION
22/09/2022
- AULA 06 - DATA FUSION - HANDS ON
22/09/2022
- AULA 11 - SECONDARY MEMORY 1
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- AULA 05 - SELF-ATTENTION
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- AULA 05 - SELF-ATTENTION - HANDS-ON
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- AULA 10 - INTERCONNECTION STRUCTURES 2
16/09/2022
- AULA 09 - INTERCONNECTION STRUCTURES 1
15/09/2022
- AULA 09 - INTERNAL MEMORY 2
15/09/2022
- AULA 04 - DOMAIN ADAPTATION - HANDS ON
12/09/2022
- AULA 08 - INTERNAL MEMORY 1
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- DOMAIN ADAPTATION - THEORY
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- AULA 07 - CACHE 3
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- AULA 03 - LEARNING 3D FROM MONOCULAR IMAGES
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- AULA 05 - CACHE 1
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- AULA 05 - CODIGOS 2
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- AULA 06 - CACHE 2
31/08/2022
- AULA 02 - BIAS AND FAIRNESS
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- AULA 02 - BIAS AND FAIRNESS - HANDS ON
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- AULA 04 - DESIGNING FOR PERFORMANCE
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- AULA 03 - CODIGOS 1
20/08/2022
- AULA 02 - COMPUTER PERFORMANCE 2
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- AULA 01 - UNCERTAINTY
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- AULA 01 - UNCERTAINTY - HANDS ON
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- AULA 01 - DESIGNING FOR PERFORMANCE 1
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- AULA 15 - UNSUPERVISED LEARNING
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- AULA 15 - UNSUPERVISED LEARNING - PRACTICE
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- AULA 16 - AUTOENCODERS
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- AULA 16 - AUTOENCODERS - PRACTICE
23/06/2022
- AULA 14 - SIMILARITY LEARNING
02/06/2022
- AULA 22 - SUPERSCALAR PROCESSORS 2
02/06/2022
- AULA 13 - GANS
27/05/2022
- AULA 13 - GANS - PRACTICE
27/05/2022
- AULA 20 - OS SUPPORT 4
27/05/2022
- AULA 20 - PROCESSOR ORGANIZATION 2
27/05/2022
- AULA 21 - SUPERSCALAR PROCESSORS
27/05/2022
- AULA 11 - OBJECT DETECTION
22/05/2022
- AULA 11 - OBJECT DETECTION - PRACTICE
22/05/2022
- AULA 19 - PROCESSOR ORGANIZATION 1
20/05/2022
- AULA 12 - INSTANCE SEGMENTATION - MASK R-CNN
19/05/2022
- AULA 12 - INSTANCE SEGMENTATION - MASK R-CNN - PRACTICE
19/05/2022
- AULA 18 - OS SUPPORT 3
19/05/2022
- AULA 17 - OS SUPPORT 2
13/05/2022
- AULA 16 - INPUTOUTPUT 4
12/05/2022
- AULA 16 - OS SUPPORT 1
12/05/2022
- AULA 15 - INPUTOUTPUT 3
11/05/2022
- AULA 14 - INPUTOUTPUT 2
05/05/2022
- AULA 10 - RECURRENT NEURAL NETWORKS
29/04/2022
- AULA 10 - RECURRENT NEURAL NETWORKS - PRACTICE
29/04/2022
- AULA 10 - RECURRENT NEURAL NETWORKS - PRACTICE
29/04/2022
- AULA 11 - SECONDARY MEMORY 1
29/04/2022
- AULA 12 - SECONDARY MEMORY 2
29/04/2022
- AULA 13 - INPUTOUTPUT 1
29/04/2022
- AULA 13 - SECONDARY MEMORY 3
29/04/2022
- AULA 09 - SEMANTIC SEGMENTATION - PRACTICE
08/04/2022
- AULA 09 - SEMANTIC SEGMENTATION 2
08/04/2022
- AULA 10 - PROBLEMS
08/04/2022
- AULA 09 - INTERCONNECTIONS STRUCTURES 2
07/04/2022
- AULA 08 - INTERCONNECTION STRUCTURES 1
01/04/2022
- AULA 08 - INTERNAL MEMORY 2
01/04/2022
- AULA 08 - SEMANTIC SEGMENTATION - PART 1
01/04/2022
- TRANSFER LEARNING - HANDS ON
01/04/2022
- AULA 06 - CACHE 2
31/03/2022
- AULA 07 - INTERNAL MEMORY 1
31/03/2022
- AULA 04 - CNN TRAINING - PART 2
24/03/2022
- AULA 05 - CACHE - PARTE 1
24/03/2022
- AULA 05 - GENERALIZATION
24/03/2022
- AULA 06 - OPTIMIZATION
24/03/2022
- AULA 07 - CNN ARQUITETURES
24/03/2022
- OPTIMIZATION - HANDS ON
24/03/2022
- AULA 02 - CNN
23/03/2022
- AULA 03 - CNN TRAINING
23/03/2022
- AULA 04- CÓDIGOS
23/03/2022
- BACKPROPAGATION - HANDS ON
23/03/2022
- CÓDIGOS (EXERCICIOS)
23/03/2022
- AULA 02 - COMPUTER PERFORMANCE 1
15/03/2022
- AULA 01 - INTRODUCTION TO DEEP LEARNING
11/03/2022
- AULA 01 - INTRODUCTION TO DEEP LEARNING - HANDS ON
11/03/2022
- AULA 01 - INTRODUÇÃO
09/03/2022
- MULTICORE COMPUTERS
30/11/2021
- RISC COMPUTERS
30/11/2021
- PARALLEL PROCESSING - PROBLEMS
23/11/2021
- PARALLEL PROCESSING - VIDEO 2
20/11/2021
- PARALLEL PROCESSING - VIDEO 1
19/11/2021
- AULA 22 - SUPERSCALAR 2
19/11/2021
- AULA 11 - OPEN SET RECOGNITION
18/11/2021
- AULA 11 - OPEN SET RECOGNITION - PRACTICUM 1
18/11/2021
- AULA 11 - OPEN SET RECOGNITION - PRACTICUM 2
18/11/2021
- AULA 12 - BIAS AND FAIRNESS
18/11/2021
- AULA 21 - OPERATING SYSTEM SUPPORT 4
12/11/2021
- AULA 21 - PIPELINING 2
12/11/2021
- AULA 21 - SUPERSCALAR 1
12/11/2021
- AULA 20 - PIPELINING 1
09/11/2021
- AULA 19 - OPERATING SYSTEM SUPPORT 3
04/11/2021
- AULA 18 - OPERATING SYSTEM SUPPORT 2
29/10/2021
- AULA 08 - PRODES PROJECT
24/10/2021
- AULA 08 - PRODES PROJECT - PRACTICE
24/10/2021
- AULA 15/16 - INPUT/OUTPUT 2
24/10/2021
- AULA 17 - OPERATING SYSTEM SUPPORT 1
24/10/2021
- AULA 15 - EXTERNAL MEMORY 3
20/10/2021
- AULA 15 - INPUTOUTPUT 1
20/10/2021
- AULA 16 - INPUT/OUTPUT 2
20/10/2021
- AULA 08 - CHANGE DETECTION IN THE ERA OF DEEP LEARNING
07/10/2021
- AULA 14 - EXTERNAL MEMORY 2
05/10/2021
- AULA 13 - INTERCONNECTION STRUCTURES 4
30/09/2021
- AULA 13 - SECONDARY MEMORY 1
30/09/2021
- AULA 07 - UNCERTAINTY IN DEEP LEARNING
28/09/2021
- AULA 07 - UNCERTAINTY IN DEEP LEARNING - PRACTICE
28/09/2021
- AULA 12 - INTERCONNECTION STRUCTURES 3
27/09/2021
- AULA 11 - INTERCONNECTION STRUCTURES 2
26/09/2021
- AULA 06 - UNSUPERVISED LEARNING 2
20/09/2021
- AULA 06 - UNSUPERVISED LEARNING 2 - PRACTICE
20/09/2021
- AULA 10 - INTERCONNECTION STRUCTURES 1
16/09/2021
- AULA 10 - INTERNAL MEMORY 2
16/09/2021
- AULA 05 - UNSUPERVISED LEARNING 1
15/09/2021
- AULA 05 - UNSUPERVISED LEARNING 1 - PRACTICE
15/09/2021
- AULA 04 - DOMAIN ADAPTATION - HANDS ON
08/09/2021
- AULA 04 - DOMAIN ADAPTATION APPLIED TO DEFORESTATION MAPPING
08/09/2021
- AULA 08 - CACHE MEMORY 3
08/09/2021
- AULA 09 - CACHE MEMORY 4
08/09/2021
- AULA 09 - INTERNAL MEMORY 1
08/09/2021
- AULA 06 - CACHE MEMORY 1
01/09/2021
- AULA 06 - CÓDIGOS 2
01/09/2021
- AULA 07 - CACHE MEMORY 2
01/09/2021
- AULA 07 - CACHE MEMORY 2
01/09/2021
- AULA 03 - DOMAIN ADAPTATION IN DEEP LEARNING - DENNIS WITTICH
28/08/2021
- AULA 05 - CÓDIGOS 1
25/08/2021
- AULA 04 - DESIGNING FOR PERFORMANCE 3
20/08/2021
- AULA 02 - ATTENTION
19/08/2021
- AULA 02 - ATTENTION - PRACTICE
19/08/2021
- AULA 03 - DESIGNING FOR PERFORMANCE 2
19/08/2021
- AULA 01 - INTRODUCTION
16/08/2021
- AULA 02 - DESIGNING FOR PERFORMANCE 1
16/08/2021
- PROJECT PROPOSAL - DOMAIN ADAPTATION THROUGH FEATURE ADAPTATION FOR CHANGE DETECTION
16/08/2021
- PROJECT PROPOSAL - DATA AUGMENTATION FOR DEFORESTATION DETECTION
16/08/2021
- PROJECT PROPOSAL - FACE ANTI-SPOOFING
16/08/2021
- PROJECT PROPOSAL - FULLY CONVOLUTIONAL SELF-ATTENTION FOR CROP MAPPING IN TROPICAL REGION
16/08/2021
- PROJECT PROPOSAL - OUTLIER EXPOSURE FOR OPEN SET CROP RECOGNITION
16/08/2021
- PROJECT PROPOSAL DOMAIN ADAPTATION THROUGH FEATURE ADAPTATION FOR CHANGE DETECTION
16/08/2021
- PROJECT PROPOSAL DOMAIN ADAPTATION THROUGH FEATURE ADAPTATION FOR CHANGE DETECTION
16/08/2021
- PROJECT PROPOSAL- FUSION OF SAR AND OPTICAL IMAGES FOR DEFORESTATION DETECTION IN TROPICAL RAINFOREST
16/08/2021
- PROJECT PROPOSAL - DOMAIN ADAPTATION FOR DEFORESTATION DETECTION USING SEMI-SUPERVISED GANS
13/08/2021
- PROJECT PROPOSAL- FUSION OF SAR AND OPTICAL IMAGES FOR DEFORESTATION DETECTION IN TROPICAL RAINFOREST
13/08/2021
- AULA 01 - INTRODUCTION
11/08/2021
- GABARITO G3
02/07/2021
- AULA 24 - RISC
30/06/2021
- AULA 23 - MULTICORE COMPUTERS
29/06/2021
- AULA 22 - PARALLEL PROCESSING 2
23/06/2021
- AULA 12 - SIMILARITY LEARNING 2
21/06/2021
- PARALLEL PROCESSING - EXERCISES
21/06/2021
- AULA 21 - PARALLEL PROCESSING 1
20/06/2021
- AULA 20 - SUPERSCALAR 2
18/06/2021
- AULA 11 - UNSUPERVISED LEARNING - PRACTICE
16/06/2021
- AULA 11 - UNSUPERVISED LEARNING
15/06/2021
- AULA 19 - SUPERSCALAR 1
14/06/2021
- AULA 18 - PIPELINE 2
09/06/2021
- AULA 19 - OS SUPPORT 4
09/06/2021
- AULA 18 - SUPORTE AO SO 3
07/06/2021
- AULA 16 - SUPORTE SO 2
31/05/2021
- AULA 17 - PIPELINING 1
31/05/2021
- AULA 09 - GANS
27/05/2021
- AULA 09 - GANS PRACTICE
27/05/2021
- AULA 10 - AUTOENCODERS
27/05/2021
- AULA 10 - AUTOENCODERS - PRACTICE
27/05/2021
- AULA 10 - AUTOENCODERS - PRACTICE
27/05/2021
- AULA 15 - SUPORTE AO SO 1
25/05/2021
- AULA 13 - ENTRADA SAIDA 3
21/05/2021
- AULA 08 - OBJECT DETECTION 2
12/05/2021
- AULA 08 - OBJECT DETECTION 2 - PRACTICE
12/05/2021
- AULA 11 - ENTRADA/SAIDA 1
11/05/2021
- AULA 12 - ENTRADA/SAIDA 2
11/05/2021
- PROJECT PROPOSAL - DEFORESTATION FROM LONG IMAGE SEQUENCES
01/05/2021
- AULA 08 - ESTRUTURAS DE INTERCONEXÃO 1
29/04/2021
- PROJEC PROPOSAL - NEURAL ARCHITECTURE SEARCH
29/04/2021
- PROJECT PROPOSAL - APPROACHING DATA IMBALANCE FOR DEFORESTATION DETECTION
29/04/2021
- PROJECT PROPOSAL - DOMAIN ADAPTATION FOR DEFORESTATION DETECTION
29/04/2021
- PROJECT PROPOSAL - FINE TUNNING OF ROAD DETECTION
29/04/2021
- AULA 10 - MEMÓRIA SECUNDÁRIA 1
24/04/2021
- AULA 07 - OBJECT DETECTION 1
23/04/2021
- AULA 07 - OBJECT DETECTION 1 - PRACTICE
23/04/2021
- HOMEWORK 3 - LSTM
23/04/2021
- AULA 06 - RECURRENT NEURAL NETWORKS
18/04/2021
- AULA 06 - RECURRENT NEURAL NETWORKS PRACTICE
18/04/2021
- AULA 09 - ESTRUTURAS DE INTERCONEXÃO 2
18/04/2021
- AULA 05 - SEMANTIC SEGMENTATION 2
08/04/2021
- AULA 05 - SEMANTIC SEGMENTATION 2
08/04/2021
- AULA 05 -SEMANTIC SEGMENTATION PRACTICE
08/04/2021
- HOMEWORK 2 - U-NET
08/04/2021
- AULA 08 - MEMORIA INTERNA
07/04/2021
- PROPOSTA DE PROJETO - SPOOFING
07/04/2021
- AULA 07 - CACHE 2
26/03/2021
- AULA 04 - CNN ARCHITECTURES 2
25/03/2021
- AULA 04 - SEMANTIC SEGMENTATION 1
25/03/2021
- AULA 04 - TRANSFER LEARNING
25/03/2021
- AULA 05: CÓDIGOS 2
20/03/2021
- AULA 06 - CACHE MEMORY 1
20/03/2021
- AULA 03 - CNN ARCHITECTURES 1
18/03/2021
- AULA 03 - GENERALIZATION
18/03/2021
- AULA 03 - OPTIMIZATION
18/03/2021
- AULA 03 - OPTIMIZATION PRACTICE
18/03/2021
- AULA 04 - PERFORMANCE 3
16/03/2021
- AULA 04- CÓDIGOS 1
16/03/2021
- AULA 02 - BACKPROPAGATION
12/03/2021
- AULA 02 - CNN
12/03/2021
- AULA 02 - CNN TRAINING
12/03/2021
- AULA 03 - DESIGNING FOR PERFORMANCE 2
12/03/2021
- ERRO
12/03/2021
- AULA 02 - DESIGNING FOR PERFORMANCE 1
05/03/2021
- AULA 01 - INTRODUCTION
04/03/2021
- LECTURE 14 - FINAL PROJECT PRESENTATIONS
23/12/2020
- AULA 26 - MULTICORE COMPUTERS
16/12/2020
- AULA 23 - SUPERSCALAR COMPUTERS 2C
11/12/2020
- AULA 25 - PARALLEL PROCESSING 2 - EXERCISE 4
11/12/2020
- AULA 25 - PARALLEL PROCESSING 2
09/12/2020
- AULA 24 - PARALLEL PROCESSING 1
04/12/2020
- LECTURE 13 - OPEN SET LEARNING - PRACTICE
04/12/2020
- AULA 22 - SUPERESCALAR COMPUTERS 1
03/12/2020
- AULA 23 - SUPERESCALAR COMPUTERS 2
03/12/2020
- LECTURE 13 - OPEN SET LEARNING - THEORY
03/12/2020
- LECTURE 12 - UNSUPERVISED LEARNING - PRACTICE 2
26/11/2020
- LECTURE 12 - UNSUPERVISED LEARNING - THEORY 2
26/11/2020
- AULA 21 - OS SUPPORT 4
25/11/2020
- AULA 21 - PIPELINING 1
25/11/2020
- LECTURE 11 - UNSUPERVISED LEARNING - PRACTICE 1
23/11/2020
- LECTURE 11 - UNSUPERVISED LEARNING - THEORY 1
23/11/2020
- AULA 19 - OS SUPPORT 2
19/11/2020
- AULA 20 - OS SUPPORT 3 2ND TRY
19/11/2020
- AULA 18B - OS SUPPORT 1 2ND TRY
18/11/2020
- LECTURE 10 - ATTENTION - PRACTICE
12/11/2020
- LECTURE 10 - ATTENTION - THEORY 1
12/11/2020
- LECTURE 10 - ATTENTION - THEORY 2
12/11/2020
- AULA 17 - INPUT/OUTPUT 2
11/11/2020
- AULA 18A - INPUT/OUTPUT 3
11/11/2020
- AULA 18B - OS SUPPORT 1
11/11/2020
- LECTURE 08 - OBJECT DETECTION - PRACTICE 2
10/11/2020
- LECTURE 08 - OBJECT DETECTION - PRACTICE 2
10/11/2020
- LECTURE 09 - MULTI OBJECT TRACKING - PRACTICE
10/11/2020
- LECTURE 09 - MULTI OBJECT TRACKING - PRACTICE 2
10/11/2020
- LECTURE 09 - MULTI OBJECT TRACKING - THEORY
05/11/2020
- LECTURE 08 - OBJECT DETECTION - PRACTICE
02/11/2020
- LECTURE 08 - OBJECT DETECTION - THEORY
02/11/2020
- AULA 16 - INPUT/OUTPUT 1
26/10/2020
- AULA 03 - COMPUTER PERFORMANCE 2
22/10/2020
- AULA 14 - SECONDARY MEMORY 2
22/10/2020
- LECTURE 07 - ANTI-SPOOFING - PRACTICE 2
17/10/2020
- LECTURE 07 - ANTI-SPOOFING - PRACTICE 1
16/10/2020
- LECTURE 07 - ANTI-SPOOFING - THEORY
16/10/2020
- AULA 12 - INTERCONNECTION STRUCTURES 3
07/10/2020
- AULA 11 - INTERCONNECTION STRUCTURES 2
06/10/2020
- LECTURE 06 - SIMILARITY LEARNING - PRACTICE 2
06/10/2020
- LECTURE 06 - SIMILARITY LEARNING - THEORY 2
06/10/2020
- AULA -08 - CACHE 3
26/09/2020
- AULA -09 - INTERNAL MEMORY
26/09/2020
- AULA 10 - INTERCONNECTION STRUCTURES 1
26/09/2020
- LECTURE 09 - INTERNAL MEMORY
25/09/2020
- LECTURE 05 - SIMILARITY LEARNING - THEORY 1
24/09/2020
- LECTURE 05- SIMILARITY LEARNING - PRACTICE
24/09/2020
- LECTURE 04 - DATA FUSION - THEORY
20/09/2020
- LECTURE 04 - DATA FUSION - PRACTICE
18/09/2020
- AULA 07: CACHE 2
16/09/2020
- LECTURE 03 - DOMAIN ADAPTATION - PRACTICE
15/09/2020
- LECTURE 03 - DOMAIN ADATATION - THEORY
15/09/2020
- AULA 06 - CACHE 1
13/09/2020
- AULA 05 - CÓDIGOS 2
09/09/2020
- AULA 04A - DESIGNING FOR PERFORMANCE 3
04/09/2020
- AULA 04B- CÓDIGOS 1
04/09/2020
- LECTURE 02 - DOMAIN ADAPTATION - DENNIS WITTICH
03/09/2020
- AULA 03 - DESIGNING FOR PERFORMANCE 2
02/09/2020
- AULA 01 - INTRODUÇÃO
01/09/2020
- AULA 02 - DESIGNING FOR PERFORMANCE 1
01/09/2020
- LECTURE 01 - INTRODUCTION
01/09/2020
- LECTURE 09 - MULTI OBJECT TRACKING - PRACTICE
01/09/2020
- PROJECT PROPOSAL : EFFICIENT SHIP DETECTION WITH SAR DATA - GAOFEN CHALLENGE 2020
01/09/2020
- PROJECT PROPOSAL : SHIP DETECTION ON SAR DATA: MULTITASK HR APPROACH- GAOFEN CHALLENGE 2020
01/09/2020
- AVALIAÇÃO DE ELE2765 EM 07 DE MAIO DE 2020
07/05/2020
- CÓDIGOS DE DETECÇÃO E CORREÇÃO DE ERRO
21/03/2020
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