176 skills found · Page 1 of 6
mdeff / Cnn GraphConvolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
chrischoy / FCGFFully Convolutional Geometric Features: Fast and accurate 3D features for registration and correspondence.
matenure / FastGCNThe sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""
fkodom / Fft Conv PytorchImplementation of 1D, 2D, and 3D FFT convolutions in PyTorch. Much faster than direct convolutions for large kernel sizes.
angus924 / RocketROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
pkumivision / FFCThis is an official pytorch implementation of Fast Fourier Convolution.
ka9q / Ka9q RadioMultichannel SDR based on fast convolution and IP multicasting
CQFIO / FastImageProcessingFast Image Processing with Fully-Convolutional Networks
Daniil-Osokin / Gccpm Look Into Person Cvpr19.pytorchFast and accurate single-person pose estimation, ranked 10th at CVPR'19 LIP challenge. Contains implementation of "Global Context for Convolutional Pose Machines" paper.
cwmok / Fast Symmetric Diffeomorphic Image Registration With Convolutional Neural NetworksFast Symmetric Diffeomorphic Image Registration with Convolutional Neural Networks
lars76 / Swift F0Fast and accurate fundamental frequency (F0) detector using convolutional neural networks
dealias / FftwppFast Fourier Transform C++ Header/MPI Transpose for FFTW3 with Implicitly Dealiased Convolutions
sw-gong / Spiralnet PlusSpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator (ICCV-W 2019)
thangvubk / FEQEOfficial code (Tensorflow) for paper "Fast and Efficient Image Quality Enhancement via Desubpixel Convolutional Neural Networks"
thomasverelst / DynconvCode for Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference (CVPR2020)
wangx1996 / Fast Ground Segmentation Based On JPCAn implementation on "Shen Z, Liang H, Lin L, Wang Z, Huang W, Yu J. Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process. Remote Sensing. 2021; 13(16):3239. https://doi.org/10.3390/rs13163239"
StarsX / NonuniformBlurAuthors' implementation of my SIGGRAPH Asia 2019 Technical Briefs (The Power of Box Filters: Real-time Approximation to Large Convolution Kernel by Box-filtered Image Pyramid) demo I (just for reference). A very fast approximation to large-kernel Gaussian blur with nonuniform blur radii, by making use of box-filtered mip maps V-cycle (theoratically related to Haar wavelet tranforms). The mathematical model can be found in the PDF file.
21Vipin / Medical Image Classification Using Deep LearningTumour is formed in human body by abnormal cell multiplication in the tissue. Early detection of tumors and classifying them to Benign and malignant tumours is important in order to prevent its further growth. MRI (Magnetic Resonance Imaging) is a medical imaging technique used by radiologists to study and analyse medical images. Doing critical analysis manually can create unnecessary delay and also the accuracy for the same will be very less due to human errors. The main objective of this project is to apply machine learning techniques to make systems capable enough to perform such critical analysis faster with higher accuracy and efficiency levels. This research work is been done on te existing architecture of convolution neural network which can identify the tumour from MRI image. The Convolution Neural Network was implemented using Keras and TensorFlow, accelerated by NVIDIA Tesla K40 GPU. Using REMBRANDT as the dataset for implementation, the Classification accuracy accuired for AlexNet and ZFNet are 63.56% and 84.42% respectively.
hukenovs / IntfftkFully pipelined Integer Scaled / Unscaled Radix-2 Forward/Inverse Fast Fourier Transform (FFT) IP-core for newest Xilinx FPGAs (Source language - VHDL / Verilog). GNU GPL 3.0.
shuguang-52 / 2018 RemoteSens FDSSCA Fast Dense Spectral-Spatial Convolution Network Framework for Hyperspectral Images Classification(Remote Sensing 2018)
