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3d-bat

3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

3d-brain-segmentation

This is a repository containing code to Paper "Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation" published at MDPI Applied sciences journal - https://www.mdpi.com/2076-3417/9/3/404 .

3d-detection-with-monocular-rgb-image

3D detection prediction in Autopilot scene with monocular RGB image. Selected Faster RCNN as basemodel and ResNet as backbone with Python.

3fabrec

3FabRec: Fast Few-shot Face alignment by Reconstruction - PyTorch implementation

abc-for-tsp

A simple Artificial Bee Colony (ABC) algorithm to solve the Traveling Salesman Problem

abcoptim

An implementation of the Artificial Bee Colony (ABC) Algorithm

accurate-head-pose

Pytorch code for Hybrid Coarse-fine Classification for Head Pose Estimation

action-recognition

recognize actions from videos using machine learning classifier(s) and suitable features. You will use UCF sports action data set here http://crcv.ucf.edu/data/ucf_sports_actions.zip. UCF Sports dataset consists of a set of actions collected from various sports which are typically featured on broadcast television channels such as the BBC and ESPN. The video sequences were obtained from a wide range of stock footage websites including BBC Motion gallery and GettyImages. The dataset includes a total of 150 sequences with the resolution of 720 x 480. The collection represents a natural pool of actions featured in a wide range of scenes and viewpoints. By releasing the data set we hope to encourage further research into this class of action recognition in unconstrained environments. Since its introduction, the dataset has been used for numerous applications such as: action recognition, action localization, and saliency detection. The dataset includes the following 10 actions. The figure above shows the a sample frame of all ten actions, along with their bounding box annotations of the humans shown in yellow.

adaptivel2regularization

[ICPR 2020] Adaptive L2 Regularization in Person Re-Identification

adnet

Code for the paper "Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels".

agrl.pytorch

[TIP2020] Adaptive Graph Representation Learning for Video Person Re-identification

ai4goodlab_combatcervicalcancer

alignedreid-re-production-pytorch

Reproduce AlignedReID: Surpassing Human-Level Performance in Person Re-Identification, using Pytorch.

ancis-pytorch

[Medical Image Analysis 2019] Attentive Neural Cell Instance Segmentation

android-demo-app

PyTorch android examples of usage in applications

android-v4l2-capture-client-demo

Demo V4l2 client ioctl usage

android_external_v4l2demo

v4l2demo for android

androidusbcamera

Universal UVCCamera library,supporting recording,pushing,etc. // USB摄像头(UVC)视频录制和图片抓拍，支持边推流边录像

anomaly_detection

This is the official implementation of "Anomaly Detection with Deep Perceptual Autoencoders".

artificial-bee-colony

A python implementation of clustering optimization using the Artificial Bee Colony algorithm

astronomical-images-classification

Recently, a massive astronomical dataset is being collected to find answers for a variety of unanswered questions about our universe by virtue of modern sky survey instruments. Unfortunately, it is impossible to work on these massive datasets manually to get effective results so, astronomers are seeking approaches to automate the human error borne

automl

Google Brain AutoML

awesome-blockchain-ai

A curated list of Blockchain projects for Artificial Intelligence and Machine Learning

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

background-subtraction

balnmp

Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB Dataset

basic_cnns_tensorflow2

A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).

basilisk

Astrodynamics simulation framework

birads_classifier

High-resolution breast cancer screening with multi-view deep convolutional neural networks

bmad

BMAD hold a Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license