Pinned Repositories
a-PyTorch-Tutorial-to-Image-Captioning
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
alpha
Automated-Fact-Checking
Automated-Fact-Checking-Resources
Links to conference/journal publications in automated fact-checking (resources for the TACL22 paper).
circus
contacts
CourseraMLStanford
cs231n.github.io
Public facing notes page
CZ3005-Artificial-Intelligence-Lab1
Restaurant_Project
Nineves's Repositories
Nineves/Restaurant_Project
Nineves/a-PyTorch-Tutorial-to-Image-Captioning
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
Nineves/alpha
Nineves/Automated-Fact-Checking
Nineves/Automated-Fact-Checking-Resources
Links to conference/journal publications in automated fact-checking (resources for the TACL22 paper).
Nineves/circus
Nineves/contacts
Nineves/CourseraMLStanford
Nineves/CZ3005-Artificial-Intelligence-Lab1
Nineves/CZ4031-Project1
Nineves/CZ3005-Artificial-Intelligence-Lab2
Nineves/CZ3006-Net-Centric-Computing
Nineves/CZ4031-Project2
Nineves/doctr
docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
Nineves/icdar-task-b
Repo
Nineves/ICDAR2019_cTDaR
The ICDAR 2019 cTDaR is to evaluate the performance of methods for table detection (TRACK A) and table recognition (TRACK B). For the first track, document images containing one or several tables are provided. For TRACK B two subtracks exist: the first subtrack (B.1) provides the table region. Thus, only the table structure recognition must be performed. The second subtrack (B.2) provides no a-priori information. This means, the table region and table structure detection has to be done.
Nineves/ip
Nineves/lender
Nineves/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Nineves/MediCareApp
Nineves/ML2021SpringHW
Nineves/mmdetection
OpenMMLab Detection Toolbox and Benchmark
Nineves/nlp_course
YSDA course in Natural Language Processing
Nineves/ped
Nineves/PYNQ
Python Productivity for ZYNQ
Nineves/recommenders
Best Practices on Recommendation Systems
Nineves/scene_graph_benchmark
image scene graph generation benchmark
Nineves/TaskStream
Nineves/tp
Nineves/URECAproject