Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.
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Updated
Dec 13, 2024 - Go
Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.
Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)
This is an official implementation for "AutoFocusFormer: Image Segmentation off the Grid".
🎥 iOS11 demo application for dominant objects detection.
Development of Deep Learning algorithms for Drivable Area Segmentation, Lane Segmentation, Traffic Sign Detection and Classification with data collected and labeled by Ford Otosan.
[WACV 2019 Oral] Deep Micro-Dictionary Learning and Coding Network
This POC is using CNTK 2.1 to train model for multiclass classification of images. Our model is able to recognize specific objects (i.e. toilet, tap, sink, bed, lamp, pillow) connected with picture types we are looking for. It plays a big role in a process which will be used to classify pictures from different hotels and determine whether it's a…
Codes for our paper "Deep Patch Learning for Weakly Supervised Object Classification and Discovery".
记录每一个常用的深度模型结构的特点(图和代码)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Fuzzy-CNN comes to help improve the results of training on small data.
NVIDIA DeepStream SDK
A guide to implementing a Convolutional Neural Network for Object Classification using Keras in Python
This repository contains sample implementation of models available from iOS developer site.
[ECCV22] Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation
Use TensorFlow and convolutional neural networks with PowerAI to classify radio signals from outer space
Object counting with Yolov7.
This repository contains the implementation of an Object Detection and Classification & Line and Circle Detection Application
A mobile robot equipped with a 6-DoF manipulator to pick up different bricks in a partially known environment: kinematics, trajectory planning & control, object localization & classification.
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