By training an end-to-end CNN model to estimate optical flow between frames of different exposures, we are able to achieve dense image registration of them. Using this as a base, we develop an efficient method to reconstruct the aligned LDR frames with different exposure and then merge them ...
关键词: Computer graphics; Computer vision; Convolution; Image coding; Image enhancement; Inverse problems; Mapping; Network architecture; Neural networks; Video recording; CNN-based architecture; Convolutional neural network; Graphics rendering; High dynamic range; Image decomposition; Inverse tone mappings...
Training supervised machine learning models like deep learning requires high-quality labelled datasets that contain enough samples from various categories
fault-tolerant, and resilience. Zhang et al. [144] developed a framework built on Apache Storm to support the distributed learning of large-scale Convolutional Neural Networks (CNN) using two datasets, that is suitable for real-time
When the DVS was used as the acquisition device, event slices had a high image quality without motion blur, hence a 1600 × 5 FCNN was adequate to this recognition task, where 24,000 FLOPs were involved (8000 multiplications and 16,000 additions). For our solution of DVS+SNN (SpiNNaker)...
Before applying the proposed CD approach, the preprocessing of multitemporal images, including image co-registration and radiometric correction, was performed on the four data sets by ENVI software. The ground truth maps were produced by visual interpretation using ArcGIS software. 3.2. Evaluation Crite...
Dividing your photo into nine equal parts can help you find a good place to focus your image by looking to the points where the dividing lines intersect. Most cameras can superimpose a grid like this to help you set up your shots. Imagine drawing a tic-tac-toe board over a photograph. ...
Cohen, A.S., Belshaw, N.S., O'Nions, R.K., 1992. High precision uranium, thorium and radium isotope ratio measurements by high dynamic range thermal ionisation mass spectrometry. Internat. J. Mass Spec. Ion. Proc. 116, 71-81.
ITM-CNN: Learning the Inverse Tone Mapping from Low Dynamic Range Video to High Dynamic Range Displays Using Convolutional Neural NetworksInverse tone mappingConvolutional neural networkWhile inverse tone mapping (ITM) was frequently used for graphics rendering in the high dynamic range (HDR) space, ...
When 𝑇=1T=1, the output is the same as using a ResNet for a single image 𝐼(𝜏)I(τ). This will be our baseline method. When 𝑇>1T>1, our task becomes to infer the state at 𝜏τ using the images from 𝐼(𝜏−𝑇+1)I(τ−T+1) to 𝐼(𝜏)I(τ). When ...