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".

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）

A guide to implementing a Convolutional Neural Network for Object Classification using Keras in Python

[ECCV22] Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation

Simple object classification project with deep-learning. We choose CIFAR10, CIFAR100 and Caltech101 as training datasets.

LossHub: Loss Functions Library for Image Classification and Detection

Computes loss between two sets of entities using the optimal assignment based on the Hungarian algorithm.

Scene similarity for weak object discovery & classification

A simple Node Red subflow for People and Pets detection in Home Automation

Dora The Mug Finder: Detection and classification of items placed on top of a table using point cloud processing and neural networks.

A Deep Learning API to classifiy type of detected bounding boxes.

Detecting and classifying objects using LiDAR data of KITTI dataset

Implementation of yoloV4 on video with opencv and python

Code and image database for IROS2022 paper "RECALL: Rehearsal-free Continual Learning for Object Classification". A algorithm to learn new object categories on the fly without forgetting the old ones and without the need to save previous images.

Code to count the number of objects detected using the picamera on the raspberry pi 3.

This repository contains a Python implementation of an object classification system using digital image processing techniques. The system can detect, count and classify objects as Good, Defective or Undefined based on their location and size.

A Deep Learning project to detect and classify INR coins