Personal Information
Organização/Local de trabalho
Washington D.C. Metro Area United States
Cargo
Computer Scientist/Project Leader at Dakota Consulting Incorporated
Setor
Technology / Software / Internet
Site
trecvid.nist.gov
Sobre
I am a computer scientist. Specialized in computer vision. My Ph.D focused on sign language automatic recognition from real-time videos using support vector machines and boosted subunits. I have experience in skin segmentation and tracking and using machine learning methods such as NN, Adaboost and SVM. Currently, I am research scientist at NIST working in TRECVID group (http://www-nlpir.nist.gov/projects/trecvid/) dealing with various video retrieval evaluation tasks.
In my spare time, I like to develop expert advisor systems using MQL for automatic trading based on AI.
Email : geo.awad@gmail.com
cell# : 240-750-9616
Specialties: Research:
Image & video processing, computer vision
Marcadores
trecvid
video retrieval
evaluation
video search
computer vision
video to text matching
#trecvid
activity detection
benchmark
multimedia retrieval
embeddings
#deep learning
ad-hoc video search
instance search
multimedia
video analysis
#video analysis
#video retrieval
nist
multimedia event detection
automatic video captioning
video captioning
multimedia understanding
movie summarization
multimedia search
spatio-temporal detection
surveillance detection
multimedia analysis
deep video understanding
movie understanding
fema
airborne video
cap
disaster scene recognition
feature detection
video classifiers
video detection
person recognition
people detection
action
evaluations
benchmarking
text embeddings
deep learning
#vtt
#video-to-text
#person recognition
#scene detection
#instance recognition
#video retireval
#video search
#activity recognition
iacc
semantic indexing
concept detection
avs
videos
datasets
trec
actev
med
vtt
localization
video understanding
video description
query by example
multimedia ad-hoc search
event detection
video hyperlinking
Ver mais
Apresentações
(23)Documentos
(1)Gostaram
(2)[DSC 2016] 系列活動：李宏毅 / 一天搞懂深度學習
台灣資料科學年會
•
Há 7 anos
Debug me
Noha Elprince
•
Há 10 anos
Personal Information
Organização/Local de trabalho
Washington D.C. Metro Area United States
Cargo
Computer Scientist/Project Leader at Dakota Consulting Incorporated
Setor
Technology / Software / Internet
Site
trecvid.nist.gov
Sobre
I am a computer scientist. Specialized in computer vision. My Ph.D focused on sign language automatic recognition from real-time videos using support vector machines and boosted subunits. I have experience in skin segmentation and tracking and using machine learning methods such as NN, Adaboost and SVM. Currently, I am research scientist at NIST working in TRECVID group (http://www-nlpir.nist.gov/projects/trecvid/) dealing with various video retrieval evaluation tasks.
In my spare time, I like to develop expert advisor systems using MQL for automatic trading based on AI.
Email : geo.awad@gmail.com
cell# : 240-750-9616
Specialties: Research:
Image & video processing, computer vision
Marcadores
trecvid
video retrieval
evaluation
video search
computer vision
video to text matching
#trecvid
activity detection
benchmark
multimedia retrieval
embeddings
#deep learning
ad-hoc video search
instance search
multimedia
video analysis
#video analysis
#video retrieval
nist
multimedia event detection
automatic video captioning
video captioning
multimedia understanding
movie summarization
multimedia search
spatio-temporal detection
surveillance detection
multimedia analysis
deep video understanding
movie understanding
fema
airborne video
cap
disaster scene recognition
feature detection
video classifiers
video detection
person recognition
people detection
action
evaluations
benchmarking
text embeddings
deep learning
#vtt
#video-to-text
#person recognition
#scene detection
#instance recognition
#video retireval
#video search
#activity recognition
iacc
semantic indexing
concept detection
avs
videos
datasets
trec
actev
med
vtt
localization
video understanding
video description
query by example
multimedia ad-hoc search
event detection
video hyperlinking
Ver mais