… a novel IDM that is based on image classification with convolution neural network (CNN)-based
classifier. The proposed method converts the time-series data into images, which …

… -IDM, which was developed by employing CNN algorithms in Python 3.7.0 environment with
orange. We selected a CNN by validating its classification … The CNN has the structure: Input …

… It is mainly used for image classification problems. ImageNet … -IDM-YOLO constituting 32
layers. State-ofthe-art detection methods FasterR-CNN, YOLOv2 and YOLOv3 with varying base …

… Our IDM method specifically trains the layers of a Faster RCNN architecture [4] with images
… image processing and then as a Reader in computer science. He became a Professor in …

… based on convolutional neural network (CNN) is proposed. The method utilizes the ability of
CNN to perform accurate image classification. … IDM based on image classification with CNN. …

… , excelling in visual tasks such as image classification, object detection, and … image
classification and object detection tasks [23]–[26]. We compare IDM-Net’s performance with CNN …

… information with the well-known IDM car-following mode. In our framework, IDM is first used
to estimate the … First, the CNN network is applied for vehicle detection, tracking and attribute …

… the advantage of 1D-CNN and LSTM to obtain better IDM performance. The … CNN is
extensively utilized on a large-scale 2D visual database such as video analysis, image recognition…

… The features of the images extracted in this study are IDM, skewness, kurtosis, smoothness,
… Implementation of a fixed-point 2D Gaussian filter for image processing based on FPGA. In …

… The performance of our IV-IDM is also superior to these CNN-based models. VGG [23], … in
the field of image recognition, which are the similar type of structure as IV-IDM in this paper. Yu …