microscopic-images

There are 0 repository under microscopic-images topic.

Keep-Passion / ImageStitch
A Fast Algorithm for Material Image Sequential Stitching
surf-gpu image-fusion image-stitching microscopic-images
Language:Python 176
funalab / QCANet
Convolutional Neural Network-Based Instance Segmentation Algorithm to Acquire Quantitative Criteria of Early Mouse Development
cnn convolutional-neural-network instance-segmentation microscopic-images machine-learning
Language:Python 30
anjanatiha / Cancer-Detection-from-Microscopic-Tissue-Images-with-Deep-Learning
Cancer Detection from Microscopic Images by Fine-tuning Pre-trained Models ("Inception") for new class labels
deep-learning microscopic-images cancer-detection biomedical-image-processing biomedical-image-analysis biomedical-applications medical-imaging medical-image-processing medical-image-computing medical-image-analysis medical-application nasnet nasnetmobile nasnet-models keras keras-tensorflow image-classification image-recognition convolutional-neural-network
Language:Jupyter Notebook 28
fbasatemur / Microscopy_Image_Stitching
Panoramic image generation from 2D microscope images
panorama image-stitching homography phase-only-correlation image-processing microscopic-images
Language:C++ 13
biodatlab / bacteria-detection
Deep Learning-Based Object Detection and Bacteria Morphological Feature Extraction for Antimicrobial Resistance Applications
bacteria drugs microscopic-images object-detection bacteria-detection
Language:Python 6
funalab / PredictMovingDirection
Convolutional Neural Network-Based Algorithm to Predict the Future Direction of Cell Movement
cnn convolutional-neural-networks cell-movement cnn-classification machine-learning microscopic-images
Language:Python 5
Benhabiles-projects / MalariaNet
A generalized deep learning-based framework for assistance to the human malaria diagnosis from microscopic images
deep-learning malaria-detection microscopic-images segmentation classification malaria
Language:Jupyter Notebook 4
laser-scanning-microscopy
melchisedech333 / laser-scanning-microscopy
🧪 Reproducing the concept of Confocal Laser Scanning Microscope. Using Arduino and easily found materials. Generating images in Grayscale just for fun.
microscope microscope-image microscope-images arduino arduino-uno confocal-images confocal-microscope confocal-microscopy microscope-control microscope-hardware microscopes microscopic-images microscopy microscopy-image microscopy-images confocal laser-scanning microscopy-data image-generation laser-scanner
Language:PHP 4
Chandra-cc / IDCBreastCancer_histopathologyImages_deepResidualLearning
IDC prediction in breast cancer histopathology images using deep residual learning with an accuracy of 99.37% in a subset of images containing a total of 7,500 microscopic images.
deep-residual-learning deep-learning-algorithms residual-learning microscopic-images idc-prediction convolutional-neural-networks grad-cam accuracy idc-dataset image-processing image-classification
Language:Jupyter Notebook 3
ustb-ai3d / automatic_inpainting
"Deep Learning based Automatic Inpainting for Material Microscopic Images" implemented by PyTorch
image-inpainting microscopic-images paper-implementations pytorch
Language:Python 2
AhmadTaheri2021 / Lithology-microscopic-images-mini-dataset
A mini dataset of lithology microscopic images. This Dataset was developed under supervision of Dr. Keyvan RahimiZadeh and in collabotion with Prof. Amin Beheshti.
classification dataset lithology microscopic-images lithology-microscopic-images
Language:Python 1
apetsiuk / microstructure-vision-based-porosity-analysis
Microstructure vision-based porosity analysis
aluminum computer-vision materials-engineering metal micropore microscale microscopic-images microstructure pore porosity porosity-analysis opencv opencv-python python
Language:Jupyter Notebook 1
hmnd1257 / threshold-mask
Recovering Microscopic Images in Material Science Documents by Image Inpainting
image-inpainting image-processing image-recovery mask maskimage material-science materialmask matrial-image-inpainting microscopic-images opencv opencvmask opencvthresholdmask
Language:Python 1
sarkerrabi / Malaria-detection-with-ML-kit
Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is detected by trained microscopists who analyze microscopic blood smear images. Modern deep learning techniques may be used to do this analysis automatically. The need for the trained personnel can be greatly reduced with the development of an automatic accurate and efficient model. In this article, we propose an entirely automated Convolutional Neural Network (CNN) based model for the diagnosis of malaria from the microscopic blood smear images. A variety of techniques including knowledge distillation, data augmentation, Autoencoder, feature extraction by a CNN model and classified by Support Vector Machine (SVM) or K-Nearest Neighbors (KNN) are performed under three training procedures named general training, distillation training and autoencoder training to optimize and improve the model accuracy and inference performance. Our deep learning-based model can detect malarial parasites from microscopic images with an accuracy of 99.23% while requiring just over 4600 floating point operations. For practical validation of model efficiency, we have deployed the miniaturized model in different mobile phones and a server-backed web application. Data gathered from these environments show that the model can be used to perform inference under 1 s per sample in both offline (mobile only) and online (web application) mode, thus engendering confidence that such models may be deployed for efficient practical inferential systems.
deep-learning malaria-detection blood blood-smears cnn model-efficiency microscopic-images mdpi
Language:Kotlin 1
TheGrycek / Tardigrada
Automatic tardigrade biomass estimation in microscopic images.
biology-project biomass deep-learning keypoint-detection machine-learning microscopic-images object-detection opencv-python pytorch yolov8 tardigrade
Language:Jupyter Notebook 1
funalab / CoND
CoND: Classification of Neuronal Differentiation
cnn convolutional-neural-network cnn-classification machine-learning microscopic-images
Language:Python 0
hassanlougithub / lipid_droplets_counting
Evaluating adipocyte differentiation of bone marrow-derived mesenchymal stem cells by a deep learning method for automatic lipid droplet counting
theano lasagne counting-objects regression microscopic-images lipid-droplets stem-cell-differentiation
Language:Python 0
cabustillo13 / Imagenes-microscopicas
Procesamiento de Imágenes Microsópicas
microscopy-images microscopic-images image-processing
Language:Python

microscopic-images

Keep-Passion / ImageStitch

funalab / QCANet

anjanatiha / Cancer-Detection-from-Microscopic-Tissue-Images-with-Deep-Learning

fbasatemur / Microscopy_Image_Stitching

biodatlab / bacteria-detection

funalab / PredictMovingDirection

Benhabiles-projects / MalariaNet

melchisedech333 / laser-scanning-microscopy

Chandra-cc / IDCBreastCancer_histopathologyImages_deepResidualLearning

ustb-ai3d / automatic_inpainting

AhmadTaheri2021 / Lithology-microscopic-images-mini-dataset

apetsiuk / microstructure-vision-based-porosity-analysis

hmnd1257 / threshold-mask

sarkerrabi / Malaria-detection-with-ML-kit

TheGrycek / Tardigrada

funalab / CoND

hassanlougithub / lipid_droplets_counting

cabustillo13 / Imagenes-microscopicas